The Pennsylvania State University. The Graduate School. School of Science, Engineering and Technology POWER OPTIMIZATION IN BLUETOOTH LOW ENERGY

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1 The Pennsylvania State University The Graduate School School of Science, Engineering and Technology POWER OPTIMIZATION IN BLUETOOTH LOW ENERGY IMPLEMENTED THROUGH A SYSTEM ON CHIP NRF51 AND APPLE NOTIFICATION CENTER SERVICES A Thesis in Electrical Engineering by Darshan N. Karnawat 2017 Darshan Karnawat Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science December 2017

2 ii The thesis of Darshan Nitin Karnawat was reviewed and approved by the following: Sedig S. Agili Professor of Electrical Engineering Thesis Co-Adviser Aldo W. Morales Professor of Electrical Engineering Thesis Co-Adviser Susan Lemieux Eskin Lecturer in Physics Thesis Co-Adviser Seth Wolpert Associate Professor of Electrical Engineering Mohammad Tofighi Associate Professor of Electrical Engineering Professor-in-Charge, Master of Science in Electrical Engineering *Signatures are on file in the Graduate School

3 iii ABSTRACT In the field of wireless communication, consumption of power has become a major issue. As more and more manufacturers embed products with scatternet support, Bluetooth Low Energy (BLE) has emerged as a key technology. Although there is a need for constantly optimizing the power in BLE devices, most of the available literature is based on over-simplified power models. This thesis presents a scheme for power optimization through a Finite State Machine (FSM) modeling. In addition, a technique called role-switching between master and slaves devices, is presented. The role-switching technique happens during advertising and scanning events in a BLE connection. The work presented in this thesis deals mainly with power and performance improvements in BLE. The power reduction and performance improvements are achieved through software control, specifically due to the proposed role-switching algorithm and the FSM model. Nordic Semiconductor s System on a Chip (SoC) NRF51 is used in this research as a base BLE device, and a set of experiments were performed using the proposed FSM Modeling through Gateway Sink Algorithm and the role-switching. Interaction of BLE devices with a smartphone is implemented by accessing Apple Notification Center Services (ANCS). Results show an average improvement of approximately % for the scanning mode and % for the connection mode in a piconet by using the roleswitching algorithm.

4 iv TABLE OF CONTENTS List of Figures...v List of Tables...ix Acknowledgements...x Chapter 1 Introduction...1 Chapter 2 Literature Review...5 Chapter 3 Background of Wireless Communication Protocols Bluetooth Low Energy...16 Chapter 4 FSM Model and Gateway Sink Algorithm FSM Model Power Model Getaway Sink Algorithm Apple Notification Centre Services (ANCS) Hardware and Software Chapter 5 Results of the Proposed Method Signal Setup Packets Analyzed Protocol Layer Connections Event Analysis on the Chip Analysis of the data Chapter 6 Conclusion and Future Work Future Work Appendix Bibliography...114

5 v LIST OF FIGURES Chapter 2 Literature Review...5 Figure 1: High detail point to point FSM Model of Bluetooth...8 Chapter 3 Background of Wireless Communication Protocols...13 Figure 2: Bluetooth Version Compatibility Comparison...13 Figure 3: BLE Link Layer Channel and Frequencies...16 Figure 4: Different PDU Channel Uses...17 Figure 5: Piconet Formation...18 Figure 6: Scatternet Formation...19 Figure 7: Protocol Stack of BLE Figure 8: Host Layer of BLE...21 Figure 9: Attribute Protocol...21 Figure 10: Generic Attribute Profile...22 Chapter 4 FSM Model and Gateway Sink Algorithm...26 Figure 11: Advertising and Scanning in BLE...26 Figure 12: Piconets...28 Figure 13: Scatternet Network formed of three Piconets...29 Figure 14: Finite State Diagram for a BLE Device...30 Figure 15: States in Connection event...31 Figure 16: Proposed FSM Model...32 Figure 17: Workflow of the FSM model represented through Flowchart...35 Figure 18: Breakdown of the workflow for role-switching...37 Figure 19: Flowchart representation of a BLE device...39 Figure 20: Flowchart of Connections...40 Figure 21: Flowchart for the sequence of events...41

6 vi Chapter 4 FSM Model and Gateway Sink Algorithm (Continued)...26 Figure 22: High-level diagram of the BLE energy model...42 Figure 23: Disconnected nodes in a piconet...50 Figure 24: Piconet formed through reference algorithm...50 Figure 25: Piconet formed through GSA...51 Figure 26: Piconet with getaways for reference algorithm...52 Figure 27: Piconet with getaways for GSA Figure 28: Network formation...53 Figure 29: UML for Path formation...54 Figure 30: Flowchart of the algorithm...55 Figure 31: Implementation Flow...59 Figure 32: The lifetime of an ios notification...60 Figure 33: Scanning UML...65 Figure 34: Connection UML...65 Figure 35: Getting address UML...66 Figure 36: Data Transmission UML...66 Figure 37: Nordic s NRF51 Module...67 Figure 38: OmniGraffle GUI Figure 39: BLE Sniffer...70 Figure 40: Wireshark s GUI Figure 41: NRFgo Studio GUI Chapter 5 Results of the Proposed Method Figure 42: Experimental Setup...75 Figure 43: Scanning Mode Events Figure 44: Connection Mode Events...77

7 vii Chapter 5 Results of the Proposed Method (Continued) Figure 45: Chip in Connection Mode...78 Figure 46: Advertising Event for NRF51 SoC...79 Figure 47: BLE Device transmitting ADV Packets...80 Figure 48: ADV Packets for NRF51 SoC...81 Figure 49: ADV Packets on SoC captured by Wireshark and BLE Sniffer...82 Figure 50: Data packets exchanged between the devices...82 Figure 51: Hopping Sequence triggered and Sniffer Initialized...83 Figure 52: Packets Sniffed between NRF51 SoC and Apple Smartphone...84 Figure 53: Advertising Signal and Data sniffed on the Chip...85 Figure 54: Scanning Request and Response...86 Figure 55: Link Layer Indicator Signal...87 Figure 56: Link Layer Feature and Response Signals...88 Figure 57: Attribute Request and Response Signals...90 Figure 58: GATT Request and Response Signals...91 Figure 59: Packets/event against time...92 Figure 60: Variation of Packets/event obtained from Wireshark...92 Figure 61: Bytes/event against time...93 Figure 62: Variation of Bytes/event...94 Figure 63: Connections UML...95 Figure 64: Protocol Data Unit...96 Figure 65: Chip in Scanning Mode at 154 mv RMS before the algorithm...97 Figure 66: Chip in Scanning Mode at 115 mv RMS with the proposed algorithm Figure 67: Chip in Connection Mode at 428 mv RMS before the algorithm...101

8 viii Chapter 5 Results of the Proposed Method (Continued) Figure 68: Chip in Connection Mode at 314 mv RMS with the proposed algorithm. 103 Figure 69: BLE Operation Modes Figure 70: Data Transmission Comparison Figure 71: Power Consumption comparison at different Intervals...108

9 ix LIST OF TABLES Chapter 3 Background of Wireless Communication Protocols...13 Table 1: Comparison of Communication Protocols...15 Chapter 5 Results and Conclusion Table 2: Calculations Appendix I Table 3: Reference data for BLE Operation Modes Table 4: Reference data for Data Transmission Comparison Table 5: Reference data for Power Consumption comparison at different Intervals..113

10 x ACKNOWLEDGEMENTS I would like to thank my advisors Dr. Sedig Agili, Dr. Aldo Morales, Dr. Susan Eskin and Dr. Seth Wolpert for their constant support and motivation throughout my thesis. The research for the work presented brings out the best in me due to the constant feedback s and guidance from them. They have been kind enough all along the way and I couldn t thank them enough for the time and guidance. I had the opportunity to work with Dr. Morales during the initial phase of my research at Penn State. It was always a learning experience while working with him. His immense knowledge in the field and constant persistence has made the research successful. Dr. Agili constantly pushed me towards the goal and when needed guided to the right resources that I needed. He constantly raised the expectations that made me work harder towards the goal. One of the things I will always remember him saying, You are very fast Darshan and I believe in you, you will definitely do it I would like to thank Dr. Susan Eskin for the constant support during the restructuring of the research and helping me write technically for the work that was done. Her constant feedback on the proof reads made this research presentable and technically what I aspired it would be. I d also like to thank the Chancellor of Penn State Harrisburg, Dr. Mukund Kulkarni who ensured that I get the best resources all along with the proper guidance and knowledge along my Masters.

11 xi A special thanks to the entire staff of School of Science, Engineering and Technology, especially the Director Dr. Rafic Bachnak and Administrative Support Coordinator Lori Ricard for constantly keeping up with my progress and guiding me along the way. A special thanks to Deb Miller, who has been like a pillar of support and motivation throughout my years at Penn State. She made the traversal through the processes not only easy but also fun. A note of appreciation to the International advisors, Donna Howard, Anna Marshall, and Ana Patricia, for the guidance all along the program and making it a fun experience for the years at Penn State. A heartfelt thanks to my dear friends Andrew Zern, Tapan Khilnani, Ramy Zaki, Justin Lipuma and Jay Pardeshi for consistently supporting and persuading me towards the right thing. They definitely made the time worthwhile and fun. I appreciate the help from Nick Sklavos and Wesley Hood during my research and guiding me through some of the complicated aspects of the research. I want to take this opportunity to thank the team at Starkey for introducing me to different areas of bluetooth communication and leading me towards the research for Bluetooth Low Energy for my thesis. I d like to convey my love and appreciation to my brother in law Mr. Avinash Bhandari and my sister, Shradha Bhandari, for being by my side through thick and thin. Although she never shows it, she is most concerned about my happenings. Her support and endless prayers over the course of my studies have played a crucial role in my accomplishments.

12 xii My brother, Ashish Chhajed has been an inspiration throughout, his concern and advice has cumulatively helped me make it to this point in my academic career. A special thanks to my fiancée Anokhi Patel for taking those numerous trips to Penn State during the research and providing the support all along. Finally, my Mom, Sangeeta Karnawat and my Dad, Nitin Karnawat merit my utmost gratitude for their diligent prayers and support in my endeavors. This thesis, for all its worth, is dedicated to them.

13 1 Chapter 1. Introduction Communication between individuals has changed drastically since the introduction of Bluetooth and Wi-Fi. Almost every device is embedded with Bluetooth and Wi-Fi capabilities. Both of these technologies are different and can be used for diverse functions. Wireless Fidelity (Wi-Fi) is used for Internet connection and Bluetooth for device-to-device communication. For example, smartphones are the most common devices in people s hands today and all of them are incorporated with Bluetooth [1]. Bluetooth was originally designed as a way to exchange data between devices over close range. However, not everyone uses Bluetooth because of its range and the number of active slave limitations. Since the introduction of Bluetooth, a new low energy feature was developed, hence the name Bluetooth Low Energy. This feature changes how people have been using and developing Bluetooth applications. Bluetooth Low Energy (BLE) operates alongside but differently than the traditional Bluetooth protocol. BLE, along with other technologies, have allowed people to use smart devices to shop, to control lighting in the room, and even to cook food when driving back from work. Bluetooth Low Energy came into existence as early as 2001 when Nokia started the research for a new technology. The Bluetooth standards now include Bluetooth Low Energy (BLE) in the specifications as an improved version of original Bluetooth.

14 2 Bluetooth Low Energy does not replace the older Bluetooth technology but supports and works with it. Bluetooth Low Energy does not only exist to connect a smartphone to a wearable device but rather to speak and transfer the information between different devices such as bracelets, watches, wearable heart-monitors, etc. by incorporating dual-mode Bluetooth chips. This dual mode allows them to speak together using Bluetooth and Bluetooth Low Energy protocols, and grant the user access to very distinctive data such as health, sport, and fitness data. However, it is not limited to such data [1] [2]. One of the major issues in wireless communication has been power consumption. In this regard, various methods to lengthen sleep times on smart devices and reduction in the connection interval between them have been investigated [3] [4] to reduce power consumption and hence to realize a smaller battery size. In addition, the authors in [3] and [4] highlighted two of the major issues: reduction of power with a tradeoff of throughput and optimizing the topology of the network through role switching of connection nodes. In [3], the authors presented a variable-granularity power model for wireless technologies and applied it to Bluetooth. They presented both point-to-point scenario and multipoint scenario with a low validation error. Their multipoint scenario was used as a reference for designing the proposed Finite State Machine (FSM) model in this thesis. In [4] the authors highlight the topology discovery mechanism for neighboring nodes in a network. In this thesis, the design of a proposed Getaway Sink Algorithm uses this topology discovery mechanism as an initial reference point to create a structural database for state retention. The model also proposes an idea of a bridge, termed as getaway anchor, for the nodes to be identified for role switching.

15 3 A Finite State Machine approach in BLE has been proposed in [5] and [6] to tackle throughput and latency. The models proposed, although successful, limit the use of these node roles and hence the network structure. The proposed FSM in this thesis introduces a getaway anchor point that acts as a bridge and hence allows changes to the node roles while creating a robust network structure. An initial FSM implemented in [3] and [4] showed power reduction in the device and lead to better battery life. That model is used in this thesis as a reference although implemented with a getaway anchor point to utilize the node roles and an algorithm is designed titled Getaway Sink Algorithm to handle the role switching. FSM improvisation algorithms have been proposed for the last few years for BLE. Research in [3] and [4] show single and multipoint scenarios that address not only piconets but also scatternet structures. In [5] and [6], the authors proposed a unique way of handling the throughput and latency through a new FSM model. This previous research on BLE power reduction show that there is definitely a need for an improved FSM. The work done in this research proposes a novel Finite State machine (FSM) model designed to reduce the power consumption on the BLE device. The proposed FSM model utilizes the connection states and modes of the BLE devices and achieves steady states with longer sleep times. As mentioned, this work also introduces a novel Gateway Sink Algorithm (GSA) to handle the role switching of the nodes.

16 4 The organization of the thesis is as follows. In Chapter 2, previous research work is discussed. In Chapter 3, a background of related wireless protocols is presented. In Chapter 4, the work done in this thesis, a novel design based on a finite state machine and graph theory to reduce power consumption, is explained in detail. It also describes the implementation of the Apple Notification Centre Services (ANCS) and explains the role of ANCS in the proposed algorithm in this thesis. In Chapter 5 details the hardware and software used in this thesis, the reasons for their choices. In addition, the analysis and results of the power reduction are also presented. Finally, Chapter 6 presents the conclusions as a summary of the proposed research findings and avenues for future research.

17 5 Chapter 2. Literature Review The vital aspect for the development of Bluetooth Low Energy from the standard Bluetooth has been to reduce the power consumption on the devices embedding them. Various methods have been proposed to reduce the power on bluetooth devices including the BLE protocol. For this purpose, measuring the average power consumption becomes vital in selecting the best components for communicating with the BLE device. Also, power consumption changes with the sequence of event dynamics that these devices experience during connections [1] [3]. In order to study power/performance tradeoffs in Bluetooth sensor networks, the network level parameters of BLE were analyzed in [4]. Their results pointed out that BLE loss handling and connection event mechanisms might cause significant degradation in the communication performance of the device [4]. These results lead, in this thesis, to the idea of developing a mechanism to handle the connection interval parameter in a way that device performance would not be degraded. Data transfer with every event is another factor affecting the power consumed by BLE devices. Even when there is no data transfer, Bluetooth uses just enough power to barely keep the links alive. To address this issue, a power model has been proposed [5] for a point-to-point case, limiting the roles of the nodes as Master and Slave. These links play a major role in the reduction of power by minimizing the activity of signals and increasing the sleep time for these nodes although limiting the use of role switching of a node.

18 6 In addition, BLE uses in-channel power sensing to avoid interference before transmitting. If the value is below the onset threshold, the channel is termed as not busy and the transmission goes ahead. On the other hand, Bluetooth interference in the IEEE standard has been studied through various experiments in [6]. Furthermore, in [7], the author researched the interference effects of BLE on the IEEE protocol. The results of these experiments suggested that the channel separation is notably influenced by interference. Hence, using closer channels accounted for interference and thus adding to the power loss. The Bluetooth Core Specification [1] highlights that using high transmit power for short ranges may cause the receiver to saturate and result in link failure. Therefore, while designing the FSM model in this research, the transmit power was varied through the Nordic semiconductor s simulation software NRFgo Studio in order to obtain an optimal operational power. The link formation during role switching is based on this operational transmit power and then incorporated in the BLE FSM design. Data presented in [8] showed that using BLE could result in device utilization of multiple years with a CR2032 battery cell. Unfortunately, this experiment was demonstrated utilizing unusable response times, for 23 bytes of data, being as long as 32 seconds. For devices communicating and transferring multiple data and acknowledgement events this may be too long, hence increasing power consumption. The solution might be using a larger battery cell although that would increase the space requirements. A better solution would require addressing the operational states in a connection shared between a BLE device and a smartphone to better utilize the available power.

19 7 Power and Quality of Service (QoS) were optimized for BLE-based communications in a recent study [9]. For a single slave system, they showed that, the master can dynamically change the connection interval and demonstrated how the connections can gracefully stay active in the case of multi-slave systems. The change in the connection interval, although useful, was limited to a single slave system. Another approach could be the handling of states and the roles of these devices to have effective communication in the same connection interval to minimize power consumption. Another power optimization algorithm was proposed in [10] that used Multi-hop networks as a framework to utilize local information in order to increase the connectivity of the network. The approximation algorithm presented in [10] uses a minimum spanning tree for range assignment. This leads to the idea of implementing an algorithmic approach where these devices can be looked at as singular values and introduce a relay for optimizing these roles. A BLE device may operate in different situations and once the connection is setup with the other device, it can operate in different modes. The different situations of operation are transmitting, receiving, Master, and Slave. The different connection modes are Park, Sniff, Hold and Page. The FSM model in this thesis concentrates on these connection modes. In [11] the authors presented their research on the optimization of a FSM design for wireless communication that showed the state transitions for Bluetooth. The two main points that are used in this research from [11] are creating a state transfer table and proper state transitions for the proposed FSM model. The model implemented in this thesis also takes into account the failsafe mechanisms in case of unwanted state transitions.

20 8 In [12] power consumption issues of Bluetooth devices are discussed in depth. Based on the target address of a packet header, the authors implement a power reducing policy that controls the scanning window size and schedule role switching that saves unnecessary energy consumption on a Bluetooth device. The authors also proposed an interesting scheduling approach for node role switching, although if expanded it could benefit from the state retention table of a BLE device for the FSM model. This research presents such a model with a state retention table implemented in the design of the FSM. Figure 1: High detail point to point FSM Model of Bluetooth; shaded states are complex states (contains substates), shaded bubbles represent logical activities. Global state of system is state of LC layer plus state of Radio layer [3]. Another approach addresses power consumption based on a FSM design [3] as shown in Figure 1, by altering the Link Controller (LC) and the state conditions based on different modes. The BLE states [3] are: Scanning, Standby, Advertising, Initiating and Connection. The state modes are

21 9 referred specifically to the connection mode; Hold, Park, Sniff and Page. They [3] presented a high level FSM design for BLE during different states and performed analysis during these states. The FSM model is depicted in Figure 1, the reader is referred to [3] for more details. The research presented in this thesis proposes a similar FSM model as [3] but embedded with a Gateway Sink Algorithm (GSA) to handle these states for the reduction of power. In order to reduce power consumption in BLE, power needs to be accurately measured during wireless communication where the sequence of events is not fixed. Hence, in this thesis, the issue of power reduction is tackled with the implementation of a Finite State Machine Model (FSM) and through the novel idea of a Gateway Sink Algorithm (GSA), by measuring power consumption at certain states. In [13] a model to measure the average dissipated power in Bluetooth was presented. The model depends on the FSM states of Bluetooth and is analyzed in LabVIEW for two different bluetooth modules. The authors based the measurement of average power on the Host Controller Interface (HCI) transport layer, particularly on the connection link between the Master and the Slave. The work in this thesis use the measurement of power on multiple HCI connection links implemented on NRF51 Module after embedding the SoC with a proposed Getaway Sink Algorithm. This allows not only implementing the algorithm but also analyzing the power measurements on the module under test (MUT).

22 10 The work done in this thesis focuses on the power consumption of the BLE device which allows analysis of events taking place between different devices. The research in this thesis addresses the following points within the design of the Finite State Machine model: i. Retention of the operational situations, either Master or Slave with a database formation ii. iii. iv. Real-time role-switching of the BLE device as a Master or a Slave Assessing these states and provide temporary signals and acknowledgments Urgent alerts to the Master in case of communication in the event of an emergency. The first point refers to the BLE device s situation of operation consisting of transmitting, receiving, Master or Slave. The retention of the device s situation becomes vital when the role switching mechanism is implemented between the nodes. All of these points will be tackled in the framework of the proposed FSM, which is described in detail in Chapter 4. Role switching is a novel idea that would consume power at the start of the operation but aids in a more robust network formation and in turn reduces power consumption. The third and fourth points listed refer to assessing the states repetitively and updating the database for the node value and providing the high priority alerts to the Master for any role changes occurring in the network. Urgent alerts are required for the change in the sleep times of the BLE device and letting the slave know when the Master needs to communicate. The goal of this thesis therefore is to address the power reduction on a BLE device and to implement a Gateway Sink Algorithm (GSA) for role switching of the nodes. A novel idea to monitor the links and interaction between a BLE device and a smartphone is proposed through ANCS. The key aspects of this thesis are as follows:

23 11 Communication Interval: The interval between a Master and a Slave when data and acknowledgements are being exchanged. The Interval ratio should be long enough to communicate an event and then go back to sleep to save power. Communication should be fast, in the order of 3 to 5 sec, for the smartphone and the BLE device to communicate. This interval is therefore dependent on the communication and the sleep cycles between the Master and the Slave. As the communication increases so does the power consumption on the device. To properly synchronize these events and reduce the power usage, this thesis proposes a novel method through the formation of a state retention table, in a Finite State Machine model, and a gateway anchor point introduced through role switching between the nodes. Power Usage on BLE device: All SoC s will have microcontrollers embedded as well as the devices they are connected to and they utilize power for various operations and events. These devices sometimes when not active can also lead to leakage currents that draw power gradually leading to power loss. In this thesis, the NRF51 SoC along with a proposed Gateway Sink Algorithm are used to create a robust network with the introduction of a getaway anchor point acting as a bridge for role switching. The number of devices implemented in the thesis are limited to the NRF51 SoC, Apple smartphone and a BLE enabled USB device by Nordic. This checking will alleviate power loss in the connected devices, leading to power savings. Current drawn: Most of the BLE enabled chips operate using batteries that limit their maximum current usage capabilities. The usage of microcontrollers with its devices can quickly exceed the maximum peak current. This is accounted for while designing the operations needed for every state in the BLE FSM during data exchange as well in the sleep states of a Slave.

24 12 A BLE device may operate in different situations and once the connection is setup with other device, it operates in different modes. The different situations of operation are transmitting, receiving, Master, and Slave. The different connection modes are Park, Sniff, Hold and Page. The FSM model in this thesis concentrates on these connection modes along with the parameters mentioned above.

25 13 Chapter 3. Background of Wireless Communication Protocols Bluetooth, like many wireless standards, uses the 2.4 GHz industrial, scientific and medical (ISM) band since it is globally free for unlicensed use [1]. Bluetooth could initially transfer data at 1 Mbit/s rate but was increased to 3 Mbit/s with the BLE. With Bluetooth 5.0; however, faster data transfer was dropped in favor of lower power consumption. To achieve this, Bluetooth Low Energy (BLE) was introduced that allows a device to sleep for longer periods, send bursts of data less frequently, and while it does not maintain connections, like classic Bluetooth, they can quickly be re-established when communication is needed again. The Bluetooth Special Interest Group (SIG) introduced profiles for BLE devices, which defines how a device works in certain applications [1]. These profiles include blood pressure services, heart rate services, and many more. This has resulted in the following: Bluetooth, BLE, which is also called Bluetooth Smart, and Bluetooth Smart Ready that supports both the protocols [14]. In order to distinguish between different types of Bluetooth standards, new logos designed by the SIG in 2011 are as shown in the Figure 2 [1]. Figure 2: Bluetooth Version Compatibility Comparison [1]

26 14 BLE uses only 40 channels, whereas classic Bluetooth uses 79. Both technologies use frequency hopping with different hopping sequence [1]. Each channel is depicted by a pseudo-random hopping sequence which is exclusive to the piconet and is set by the Bluetooth address of the master. The channel is split into time slots. Every slot corresponds to a single RF hop frequency. Hence, different RF frequencies have corresponding consecutive hops. The standard defines two kinds of links between master and slaves: Synchronous Connection-Oriented (SCO) link, and Asynchronous Connection-Less (ACL) link [1] [11]. In the next section a brief review of power consumption and radio frequency usage for different wireless protocols and description of Bluetooth technology are presented. Table 1 depicts different wireless protocol characteristics. From Table 1, it can be deduced that among these wireless protocols, BLE, ZigBee and Z-wave are the most power efficient, Bluetooth is good and Wi-Fi is the least efficient. Hence, from the power consumption standpoint, BLE, ZigBee and Z-wave are the best candidates.

27 15 Standard ZigBee Bluetooth Wi-Fi Bluetooth low energy Z-Wave Topology Mesh, star, tree Star Star Star Mesh network & source Routing Frequencies of 868 MHz, 2.4 GHz GHz 868 MHz operating 915 MHz, GHz 2.4 GHz 5.8 GHz Range 100m >100m 150m Up to 50m 30 m Battery Life Months to years Days to weeks Hours Years Months to years Table 1: Comparison of Communication Protocols Regarding radio frequency, BLE, ZigBee, Bluetooth and Wi-Fi use 2.4 GHz, which is license-free and Z-Wave uses 868 MHz. An advantage of BLE and Bluetooth is that, because of their adaptive frequency hopping, they can coexist with Wi-Fi. However, ZigBee cannot. In addition, ZigBee is not available on general-purpose devices, like mobile phones, PDAs or personal computers [3] [4]. This makes ZigBee less appealing from an infrastructural viewpoint. Thus, it is clear that, BLE is the most suitable wireless communication protocol for the next generation of intelligent systems over short to medium range (up to 50 meters).

28 Bluetooth Low Energy To restate terms, since it is somewhat confusing, Bluetooth Low Energy or Bluetooth LE or BLE, is marketed as Bluetooth Smart. BLE was designed to be more energy efficient than classic Bluetooth [2]. BLE saves energy with the way the frequency channels are utilized. There are only three transmitting channels as shown in Figure 3. Bluetooth LE distinguishes between channels used for transmission and reception. Listeners only have to listen to three special transmitting channels, distributed evenly over a total of 40 channels, before deciding to connect. Figure 3: BLE Link Layer Channel and Frequencies [1] BLE has 37 channels for data transmission. A BLE device may operate in different situations depending on the functionality such as transmitting, receiving, Master, or Slave. In order to establish a connection, one device has to be in transmitting mode and the other device in receiving mode. The receiver scans for a device-transmitting packets and sends a connection request.

29 17 A basic BLE packets include a 1-byte preamble, 4-byte access codes correlated with the RF channel number used, a Protocol Data Unit (PDU) between 2 to 39 bytes and 3 bytes of Cyclic Redundancy Check (CRC). The different PDU channels are shown in Figure 4. Figure 4: Different PDU Channel Uses [1] The size of the PDU can differ from 2 bytes to 39 bytes, implying the shortest packet can have 80 bits (1-byte preamble + 4-byte access codes + 2 PDU bytes + 3 CRC bytes), and the longest one has 376 bits and can be transmitted in 0.3 ms [1] [11]. A transmitting interval is the interval between the transmissions of consecutive packets and can be set in the range of 20 ms to 10 s. A transmitting device has a PDU with a 16-bit header and up to 31 bytes of information as shown in Figure 4.

30 18 Bluetooth is a low power, low-cost, short-range wireless technology [1] where devices form piconets, and in turn with bridges form scatternets. In a piconet, one device is the master and the other devices act as slaves and share the same channel [1] as shown in Figure 5. By a polling scheme, the master coordinates among one to seven slaves in a piconet. Each piconet has its own hopping sequence that is controlled by the Master. The Master device transmits packets in even slots and the Slave devices transmit packets in odd slots. A device that participates in multiple piconets providing connectivity between them is called a Bridge. Several piconets connected by common bridges form a connected scatternet. The bridge device can relay packets from one piconet to another. Figure 5: Piconet Formation A well-structured scatternet has more than eight devices to form an interconnected piconet in a communicative range and number of bridges being assigned proper roles as shown in Figure 6. As the number of piconets is increased, the hopping sequences of the two devices that are in different piconets are likely to collide with each other [1] [2], increasing the probability that a packet is lost and reducing the performance of the scatternet by requiring packet retransmission. Increasing the number of piconets also increases the path to each node, delaying the construction of the route and the transmission of packets, and hence increasing the power consumption of the device. When the

31 19 packet collision rate exceeds a threshold, appropriately reducing the number of piconets will improve the performance by reducing the packet error rate and the route length [1]. Figure 6: Scatternet Formation In the next sub-section, the Bluetooth stack protocol is described that allows the exchange of communication between the different devices with the formation of a piconet and scatternet.

32 Protocol Stack The protocol stack is divided into different components. HCI acts as intermediatory channel between the Host Layer and the Controller as can be seen in Figure 7 [1]. Figure 7: Protocol Stack of BLE [1] (a) BLE protocol stack; (b) Frame format The Controller architecture for BLE has the Link and Physical Layer along with the HCI. Both layers act as a radio which can be controlled by the Host Controller Interface [1].

33 21 The host has different layers that are depicted in Figure 8. These layers are explained below: Figure 8: Host Layer of BLE [1] Logical Link Control and Adaptation Protocol (L2CAP): The disintegration and integration of data is done at this layer for BLE. It has three channels ATT, L2CAP and SM [1] [11]. ATT: BLE majorly communicates via addresses and these addresses can take different roles. The data communicated between two devices having permissions and rights is termed as attributes and shown in Figure 9 [1] [11]. Figure 9: Attribute Protocol [1]

34 22 Generic Attribute Profile (GATT): GATT is a profile used to shape these attributes. It defines the usage of services the device has to offer. E.g. Thermostat can have temperature services defined [1] for different devices. GATT is as shown in Figure 10. Figure 10: Generic Attribute Profile [1] Generic Access Profile (GAP): GAP defines as to how the devices connect to each other and how they communicate with each other. GAP consists of explicitly forming a connection known as the Connecting Mode to transfer data and the Broadcasting mode where an explicit connection is not required for data transfer.

35 Communication channels BLE has communication architecture that consists of attributes, services and profiles as the end user data channels. According to the specification few attributes defined are [1]: 1. Requests: Master Reads (R) / Writes (W) and Slave Acknowledges (SA) 2. Commands: Master Reads (R) / Writes (W) and Slave doesn t Acknowledge (SNA) 3. Indications: Slave sends Attribute value (AV) and Master Acknowledges (MA) 4. Notifications: Slave sends Attribute value (AV) and Master doesn t Acknowledges (MNA) 5. Universally Unique Identifier (UUID): To primarily identify BLE devices, 128 bits or a string of 16 Octets expresses a universally unique identifier. Since the UUID accounts for most of the transmitting package, it eliminates the likelihood of two groups sharing the same UUID. An address acting as a handle tied to some value of a peripheral is used as an attribute. An attribute gains meaning only when it is discovered using the GATT. The central device can then know the meaning. One UUID can have multiple attributes [11].

36 Connections and parameters In Bluetooth Low Energy, communication of relevant information is spaced out at different intervals. During a connection, certain connection parameters are negotiated between the peripheral and the central device that should be used until the next negotiation [11]. 1. Transmitter Interval: A device transmits its location and is available for connection at transmitting points. It then waits for another device after sending short bursts of data to mark itself for connection. 2. Anchor Point: In BLE, certain points where data is communicated between the devices is called anchor points. Either or both devices can save power by using this as a point of contact for data to be transmitted and thus stay in the Sleep mode for a longer time. 3. Connection Interval: Connection interval is the time between the anchor points. 4. Connection Slave Latency: Master device needs to be transmitting until a connection is established, however other devices can ignore this broadcasts if they aren t interested in connecting with this device. The time for the Master to connect to the Slave id thus coined as the Connection Slave Latency. A Slave is thus always required to be active if it encounters an Anchor point. The protocol dictates that both devices must wake up, transmit and receive data at these negotiated anchor points. Note that because of the low power consumption constraint, BLE has a smaller time window for data transfer.

37 25 This thesis focuses on the power consumption of a BLE device. The BLE device defined in this thesis is incorporated, with a novel FSM Model explained in Chapter 4, to connect and communicate to a smartphone. A unique Gateway Sink Algorithm (GSA) to handle the role switching of the nodes is further explained to help reduce the power consumption on the device with improved formation of piconets. To implement the BLE connections, an Apple s smartphone is connected to a Nordic s SoC NRF51 through a unique method proposed via the interaction of Apple Notification Center Services. The SoC is programmed, through the NRFgo software Studio. Experiments performed in this thesis use BLE Sniffer and Wireshark software to sniff the packets exchanged over the air. In short, the aim of thesis is to implement a solution to access the notifications on a smartphone using BLE and be able to perform actions on them, and embedded on top of an FSM model for power reduction.

38 26 Chapter 4. FSM Model and Gateway Sink Algorithm According to the Bluetooth Low Energy standards, there are 3 channels out of 40 channels used for advertising, numbered 37, 38 and 39 as shown in Figure 11. The time between two advertising events is termed as advertising interval and the time frame between two scanning events is termed as Scanning Interval [1]. Figure 11: Advertising and Scanning in BLE Once the scanning and advertising events are transmitted, the device advertising receives a connection request from the scanner. The connection once established, makes the advertiser the Slave in the connection and the Scanner the Master. Master and Slave connection thus forms what is known as piconet.

39 27 During a Bluetooth connection, devices hop on different frequencies in a sequence that they predecide to use after the transmission of each packet [1]. The operation involves the devices to operate in two modes; Master and Slave. Here, the device acting as the Master sets the sequence for frequency hopping. The devices acting as Slaves follow this hopping sequence by synchronizing with the Master in time and frequency. There is a unique address and clock associated with every Bluetooth device. This address and clock can be used to calculate the frequency hop sequence, which is described as an algorithm in the Bluetooth Specifications [1]. The Master s clock and address are sent to the slaves when they connect to the Master. Once the slaves know the clock and address of the Master, they then calculate the frequency hop sequence from that. Here as the Master s clock and address are used by the slaves, all are synchronized to the Master s frequency hop sequence. The Master not only controls the frequency hop sequence, but also decides which devices are allowed to transmit. The Master controls this by allocating slots for voice and data traffic to slave devices [1]. The Slave transmits in data traffic slots only when replying to the Master s transmission. On the other hand, slaves use voice slots, where they are required to transmit in reserved slots, regularly even if not replying to a transmission from the Master. The total bandwidth is controlled by the Master, as to how it is divided depends on which slave is required to communicate for how long. The data transfer requirements decide the number of time slots for each device. Dividing the time slots here between multiple devices is known as Time Division Multiplexing (TDM).

40 28 The role played by piconets and scatternets is important in a network formation once the roles are decided as either Master or Slaves. The focus of this thesis is utilizing these network formations and introducing an algorithm for optimum utilization of such formation. A point-to-point connection has only one single device connected to a Master and a point-tomulticast connection involves multiple devices connected to the Master as shown in the Figure 12. Figure 12: Piconets (a) Point to point piconet (b) Point to multipoint piconet In a piconet the Slaves are not connected to each other, they only have a link to the Master. There is always a shared Master when operating in a point-to-multicast connection and the specification limits the number of slaves to seven in a piconet. By linking piconets for a larger area or a greater network, a scatternet can be formed where few of the devices are members of more than one piconet as shown in Figure 13. A device does time-share when it is present in more than one piconet of a scatternet. The device needs to spend a few time-slots in all the piconets that device is shared between. As shown in Figure 4 (on page 19), the device spends a few time-slots in one piconet as a Slave and then the other piconet it spends a few time-slots as the Master. As all the Slaves in a piconet are synchronized with the Master s clock and address, there cannot be a device which operates as Master in two different piconets. As is defined, devices on the same piconet should have the same Master.

41 29 Figure 13: Scatternet Network formed of three Piconets When dealing with scatternets, which involve multiple piconets, connected together, it is important to account for interference. The major source of interference will be other Bluetooth devices. Synchronization will definitely deal with devices on the same piconet but unsynchronized piconets in the same area can cause collisions if they operate on the same frequency. This will result in the loss of packets and thus in retransmission. More retransmission will therefore be required in case of multiple piconets in the same area causing the data rates to fall [14]. This can be compared to a real-time problem of multiple people talking in a conference room at once. The more people, the noisier it gets and a person will have to keep repeating himself to get his ideas through to the other people similar as the data packets that are sent between the devices on the piconet. To deal with synchronization among devices, an algorithm along with a priority database is proposed in a later section. A Finite State Machine is paired with this algorithm to improve synchronization. Results of this improvement will be shown in Chapter 5. The next section describes the Finite State Machine model proposed for this research.

42 FSM Model State machines are used to implement decision-making algorithms. A finite state machine (FSM) is based on the idea that a given system has a finite number of states. The state diagram for the Link Layer of BLE is shown in Figure 14[1]: Figure 14: Finite State Diagram for a BLE Device [1] The Link Layer controls the FSM operation for a BLE device. The Link layer shall always support one of two states, Advertising or Scanning. None of the packets being transmitted or received are obtained by the Standby state. Transmission of advertising packets is achieved by the Advertising state. A device listening to these advertising channel packets is said to be in Scanning state. On the other hand, a device listening for these advertising channel packets from a particular device to form a connection is said to be in Initiating state. A Connection State when entered through the Initiating state terms determines the role of the device as Master, however; if entered from the Advertising State, then the device role is Slave [1][3].

43 31 The model proposed in this thesis addresses the transition time and the delays in the connection between a central and peripheral i.e. a Master and a Slave. Once the connection is established between a Master and a Slave, the radio activity between the two increases resulting in consumption of power. Each event between the Master and Slave is termed in this thesis as a transition. A power model is then introduced that decides the most conservative linkage of the nodes based on the least number of transitions required for the transitions to occur. The linkage deals with the nodes in either Active or the Sniff Mode, which is used to reduce the transition time. A node is said to be in Active mode, in this thesis, if it is in a connected state and ready for transmission of events while a node in Sniff mode is in less active state where it will sleep and listen for transmissions every fixed time interval. Figure 15: States in Connection event [1] The states model is applied based on the tree structure in a scatternet. The research in this thesis addresses the delay issues though limiting the optimization of the throughput in a given scatternet. From Figure 15, the Advertiser and Scanner enter Inquiry and Inquiry Scan phase. An ID packet is exchanged between the two devices and the Scanner sends the Frequency Hopping Scheme (FHS) Packet to decide the synchronization between the devices in the connection. The initial step

44 32 in the proposed Getaway Sink algorithm described in detail in the next section is the recursive search to formulate the best configuration for the scatternet. Hence, static number of nodes creates the best-case scenario while implementing the technique. The main objective of this research is optimizing the scatternet formation to assign the roles i.e. Master or Slave and thus creating a priority database to handle the constant changes and implement role switching during the transitions. Scatternet optimizations majorly deals with decreasing the number of Masters in a given piconet for the transitions to smoothly and effectively communicate. This has the effect of reducing the overhead of constant changes and in turn decreasing the number of piconets [16] [17]. Throughout this research, and during implementation of the algorithm, more time was spent on the role of the Master. It is simpler to implement optimization just by decreasing the number of Masters than slaves and thus making a scatternet more flexible. Figure 16: Proposed FSM Model The Model implemented in this research is as shown in Figure 16. Figure 16 is a breakdown of the transitions and states once the connection between devices is established according to the Bluetooth standard [1]. The states of a BLE device start from Standby and end either in a

45 33 connection or in the same state. The Connection state once achieved goes through four different states; Active, Hold, Park and Sniff. The research in this thesis focusses primarily on these states. These connection states further are divided into Master and Slave roles along with the action they are involved in. As can be seen from Figure 16, the nodes determined as Master and Slaves are further classified by reception or transmission of an event. The classification is necessary to optimize the power consumption on the device by minimizing the transmission once the number of Masters in a scatternet is reduced and the sleep time for the Slaves is increased lowering the reception activity and hence reducing power consumption. The focus on the connection states in the model is such that the radio activity of the Master and the Slave is monitored as the roles keep switching through the Park and Hold modes and reported back to the database. The last stage of the FSM links the transmitting and receiving activity of the Master and Slave nodes in a way where only one state is handled at a given interval of time. The results of the improvements of the proposed model, in terms of power consumption and throughput, are presented in Chapter 5. Most of the algorithms implemented over the years for creation and steering of scatternet are based on the utilization of the power through a simplistic design and through standard s specifications. In [18], the authors suggested that the slave with one slot consumes 1 unit power while receiving and 2 unit while transmitting. The approach of handling the event transitions and the linking of nodes is slightly changed while using the Gateway Sink Algorithm proposed in this research.

46 34 The FSM model proposed for the connection states is paired with the GSA algorithm with a matrix formation for the linkage of the nodes. This matrix formation is based on the role of the nodes and the transmission activity logged on the priority database. A database is then created through the GSA algorithm to log these states and the level of activity of the nodes. This process is explained in the next section. Define the power usage by the Master as Pm, Slave Ps, Advertising Events Padv, Scanning Events Pscan and the power usage during the interval between the transitions Pi form a utility matrix model P1. P1 here is initially created to form a rough metric of all the parameters and then is used to populate a definitive matrix P2. The matrix P1 thus becomes a helper matrix in order to create a more definitive matrix P2. P2 matrix is created to identify the number of transitions for each node in a given piconet. It uses all the activities the node is involved in, in order to populate the matrix. The point of creating a power model matrix P1 and P2 is to breakdown the transitions for a node and create a power matrix based on the events that the nodes are involved in. P2 matrix is formed by extrapolating the utility matrix P1 and then comparing the distances in reference to the root node in the scatternet.

47 35 The workflow for the model is represented through a flowchart in Figure 17. Figure 17: Workflow of the FSM model represented through Flowchart Once the matrix P2 is formed, the topology established for the network needs to be optimized for the optimal use of the roles. The point of creating a power model matrix P1 and P2 is identifying the number of transitions for each node in a given piconet. The tracking of power levels and the transitions is accomplished through a Value Assignment and Database Formation (VADF) implemented through the GSA algorithm explained in the next section. Once the nodes for role-

48 36 switching are analyzed through the VADF, this research proposes a structure formation for the devices to quickly identify the transitions between devices. This helps in reducing the events and transitions between the devices as the database is used as a quick reference whenever the node has to do a role-switching in case of acting in a different piconet of a scatternet (see Figure 13). These nodes once analyzed are structured as a tree based on their database value for quick role-switching and retrieval of the node value. The path route model and the linear check for the network formed are derived along with the optimization of the communication interval between the events. The algorithm for the FSM is recursively applied to form a tree topology. A delay Dm is introduced in the FSM model designed to monitor the time between the links switching of the nodes. When Dm starts decreasing, and in order to achieve power reduction, the link switching between the nodes is modified as follows: I. Nodes in active state stay connected until an acknowledgement is received. II. As the linking of nodes appears between Master to Slaves and during the role-switching where a Slave in one piconet becomes a Master in another piconet the following procedure is performed: a. The nodes becoming active in the first iteration are the ones with greater number of child nodes forming the scatternet and followed by the creation of leaves and branches. b. Leaf nodes i.e. the nodes with no child, groups the nodes w.r.t to Dm and using the distance from the database as reference.

49 37 The breakdown of the workflow is shown through a flowchart in Figure 18. Figure 18: Breakdown of the workflow for role-switching When in idle mode, all the nodes in the network are passively scanning for transmissions. These nodes are the part of the scatternet in which different piconets are communicating. When a node in a different piconet has the need to transmit data towards the gateway, it goes into the advertising

50 38 mode. The node receiving the advertisement initiates the connection and therefore it becomes the Master, and the node with the data becomes the Slave of the connection. The getaway node is the node which is a Slave in one piconet and Master in another as shown for the node b in Figure 13 (on page 32).

51 39 Once the connection is formed between two devices then the roles are setup as Master for the device scanning for the connections and Slave for the device in the advertising state. The bond being formed between the devices, gives rise to implement the solution for optimization as the devices in a connection increase and more number of signals are exchanged between the devices. Figure 19: Flowchart representation of a BLE device [1] The representation of the signals for the initial setup between the BLE devices is as shown in Figure 19. The device information is exchanged once the connection request is received and is stored in the database as reference and in the device for the connection time for further communication.

52 40 The visualization of the flow of the connection is as depicted in Figure 20. Figure 20: Flowchart of Connections After the slave accepts the connection, the encryption of the link starts. Now that the link is up and encrypted, the master reads the data from the slave s GATT. Once the data is read and confirmed, the connection is closed and both nodes go back to the scanning mode.

53 41 Figure 21: Flowchart for the sequence of events The flow of connections for the FSM model proposed is shown in Figure 21. The acknowledgement signals for the connections are so chosen to reduce the flow of reception between the devices. After the initialization of the first FSM, transitions occur from the respective state to another state machine to check the category of the events. In Figure 21, below the flowchart gives us the basic idea of how the proposed FSM works. It starts with initializing the parameters of the nodes and creating a database with the Role Switching Rate from the Value Assignment and Database Formation (VADF). The sequence of signals becomes vital when a node is switching roles and forming links as the formation changes.

54 Power Model In Figure 22, a high-level view of the BLE power model is shown [12]. The BLE protocol can be modeled as a temporal sequence of single events that happen periodically. Energy models of these events depend on their type (connection, advertising or scan event), as can be seen on the left in the figure. The hatched boxes in Figure 22 depict protocol parameters that are fed into the model. Figure 22: High-level diagram of the BLE energy model. The hatched boxes denote BLE protocol parameters used by the model [12] This model is used as reference to implement the proposed FSM model for analyzing the scan and advertising states and their behavior. The energy consumed per event is multiplied by the number

55 43 of times an event occurs and the results for different events are then summed up. In addition, the time the device sleeps between these events and its corresponding sleep energy consumption is calculated. By combining the energy consumed by of all events with the energy spent during sleeping, the expected energy for transmitting a given payload for a given set of parameters is also calculated. This procedure occurs when either the scanner has discovered a remote device and establishes a connection or connection parameters are to be updated in an existing connection. The most common technique in saving power on embedded (wireless) devices is reducing the MCU awake times by either limiting the wakeup time for radio communication on a low level [19] or by limiting the power usage of the MCU by lowering the operating voltage [20]. In wireless devices, this can be combined with higher-level network protocols to make sure the device is not awake for too long or takes too long to listen to other devices as the transmitter usually consumes an equal or greater amount of power than a receiver. Other methods are limiting transmission power or receiver gain, but those only limit the power consumed during transmission by a small margin and are still dependent on the amount of time the device is awake. The technique implemented in this thesis is based on the use of the low power mode in BLE [12]. The modes of BLE has different power consumptions and the optimization of Advertising, Scanning Interval times lead to effectively improving the power consumption of the device. The average power consumed is based on the advertising interval τadv_int which is an integral multiple of ms in the range of 20 ms to 10,240 ms [1], and by the scanning interval τscan_int which is also an integral multiple of ms in the range of 2.5 ms to 10,240 ms [1].

56 44 Consider two parameters to analyze the modes of operation for the devices, power usage by the Master and the Slave respectively Pm and Ps, for Sniff, Hold or Park modes of operation. These modes do not involve any data transmission between the master and the sniffing slave, but could involve data transfer to other slaves, and thus termed as power saving modes. The data start is only for the Master s power w.r.t to other slaves and their operation. There is no data transfer in sniff mode for the slave. It s calculated in the power for Sniff as the Master is still involved in the transmission. Consider a device operating in a Slave mode and a varying Pm based on the scatternet formation. The power consumed by a Slave and Master during a Sniff connected mode is as, P s sniff = P s sniff_interval + P s sniff_initiated + P s sniff_terminated P m sniff = P m data_tx_other_nodes + P m sniff_terminated P sniff total = P sniff sniff s + P m In the hold mode, the master stays there until the connection is terminated. The power consumed changes for the terminated state as the Master communicates with the slave before terminating the hold and then the data transmission starts from the other slaves once the hold is terminated. The equations below take into account the overall effect of modes and the changes to modes based on the role changes in the network.

57 45 The power consumed by the Slave and Master during a Hold connected mode is as, P s hold = P s hold_req + P s hold_initiated + P s hold_terminated P m hold = P m put_in_hold + P m hold_terminated + P m data_tx_start P hold total = P hold hold s + P m In a similar manner, the power consumed by the Slave and Master during a Park connected mode is as, P s park = P s park_resynchronize + P s park_initiated + P s park_terminated P m park = P m other_slave_trasitions + P m park_terminated + P m data_tx_start P park total = P park park s + P m As proposed by [14], power in a BLE device during a Sniff mode could be added as two power component i.e. one from the master and the other from the slave as per equations 3, 6 and 9. Since the sniff mode is the most significant with respect to power consumption, better power savings can be handled w.r.t the interval time of the sniff mode as well as the initiation and termination of this sniff mode [22]. Also, only when P m sniff and P s sniff go below a minimum threshold the effect of power optimization becomes negligible. From Equations 3, 6 and 9 above we get, where P slaves modes, is the power consumed on a Master-Slave pair device. modes sniff sniff active active park hold P total = P m + P s + P m + P s + P total + P total 10 Note that a device is said to be active when it is not in a Sniff, Park or Hold mode. We also account when the master device is either communicating with other devices or busy receiving the data from other devices. Hence, the active mode is used in this research to analyze the power consumption for data transmission. Note that in equation 10, the master-slave pair will be only in one of the 3

58 46 states (sniff, park or hold) at any given time. This will be handled at run-time and by checking the mode which will be then combined with active state power. The overall power for a scatternet from [21] [23] can be written as, slaves N = j=1 P total (1 j) P sniff m + N k=1 (1 k) P sniff s + 0 P sniff s + (1 0 ) 0 (P sniff m P sniff N s ) + (1 δl) P l=1 total N park + (1 m=1 hold Γm) P total 11 The reader can notice that in equation 11, we have included some power from masters. Ideally, power on the masters are all zero, but in reality, some minor power is consumed. To be more realistic, in equation 11 these powers are included. The overall power for a scatternet then comes to be, M+S N = j=1 P total (1 j) P sniff m + N k=1 (1 k) P sniff s + 0 P sniff s + (1 0 ) 0 (P sniff m P sniff N s ) + (1 δl) P l=1 total N park + (1 m=1 Γm) P hold total + N l=1 (1 active γn) P total Where, 12 N j=1 (1 j) P sniff m = Power consumed by Masters during Sniff mode N k=1 (1 k) P sniff s = Power consumed by Slaves during Sniff mode N l=1 (1 park δl) P total = Power consumed during Park Mode

59 47 N m=1 N l=1 (1 (1 hold Γm) P total = Power consumed during Hold Mode γn) P active total = Power consumed during Active Mode As shown in Equation 11, the power calculated refers to the consumption of power on the Slaves w.r.t the algorithm implemented. The components account for Sniff, Hold and Park connection modes for the slaves in the scatternet. Equation 12 whereas takes into account the total power on the slaves and also adds the Active power component that is linked with the data transmission signals and the acknowledgement signals with the Master. The research in this thesis focuses mainly on the Sniff mode as the mode is majorly involved in power consumption of the device and the power consumed at different intervals by the slaves compared to the active mode power consumption. and β are binary variables, for example can be one when in the active mode. j is the link to the j-th Slave and k is the link to the k-th Master. Active mode relates to the data transmission interval between the Master and the Slave, i.e. when the link between them is active. The algorithm uses these variables as flags to know what link is in active or sniff mode and to determine the power consumption of the node based on their value.

60 Getaway Sink Algorithm (GSA) This section talks about the formation of the network along with utilization of the device characteristics to be able to assign the role and switch it when required. The role switching becomes necessary as multiple parameters in a BLE i.e. power during the connection modes viz. Sniff, Park and Hold modes, scanning and advertising intervals and memory are affected because of it. The Getaway Sink Algorithm, which allows for power management, is explained below and the reasons for its choice follow it Proposed Algorithm The proposed algorithm is hereby named Getaway Sink Algorithm. For comparison, the Breadth- First Search (BFS) algorithm [24] [25] is chosen as the reference algorithm. The important highlights of this algorithm are the link formation, faster connectivity and the role switching implemented on top of a FSM Model as described in Section 3.4. An initial scan of the network is performed to formulate a base table of values for all the nodes. These are then utilized in the role-switching architecture based on the energy in the node. A Node database is thus an initial scan of the network to produce the optimal roles for the nodes in connectivity.

61 49 The algorithm treats each node as a singular integer value, which is unique and constant, and the network formed by the devices uses these values. The algorithm construction is divided in two parts: 1. Value Assignment and Database Formation (VADF) 2. Piconet Structure and Connections In Value Assignment and Database Formation (VADF), the algorithm runs an initial scan through the NRF51 chip before assigning the roles, to initialize the structure. After the initial scan, a pseudo network structure is generated for the formation available, singular values are assigned to all the nodes in the event, and a database is formed. This assignment and database formation is termed as VADF. The next step is the formation of the links between the nodes and the energy values assigned to the nodes. This structure is important for assigning the roles, which assigns a unique value, based on the energy of the node and the distance between the node and its neighbor s.

62 50 Reference Algorithm Figure 23 below shows an example of a piconet where the initial phase is the discovery of the neighbor nodes. The node in unit distance is defined as a neighbor. The next step is assigning a unique identifier for all the discoveries based on the random selection of the Master node. Figure 23: Disconnected nodes in a piconet The formation of the network topology is as shown in the Figure 24. As seen Node 3 and Node 7 are chosen to be the Master nodes in the respective piconets. This limits the optimal choice for the selection of the node and hence affects the overall performance of the device as the Master drives the major signals. Gateway nodes 4 and 5 are controlled by their respective Masters 3 and 7. Figure 24: Piconet formed through reference algorithm

63 51 The same topology implemented through the Getaway Sink Algorithm is shown in Figure 25 and the Nodes 2 and 6 are chosen as the Master nodes based on the energy and the distance from the neighboring nodes. The approach allows to choose the Master based on the distance and energy chosen by the algorithm. Figure 25: Piconet formed through GSA

64 52 The Getaways linking the network implemented through the reference algorithm are as shown in the Figure 26. The red arrow links the two getaways connected in the scatternet. The approach increases the signals that are used for communication. Figure 26: Piconet with getaways for reference algorithm The same after using the VADF, creation of the database for the formation of the links is as shown in the Figure 27. The capturing of the nodes is reversed as shown with the red arrow as it depends on the role switching between the nodes. The link is chosen to reduce the connection interval between the nodes. Figure 27: Piconet with getaways for GSA

65 53 In Figure 28, a network is shown with the function of finding the best route from node 1 to Node 6. The possible paths are varied as the links in the network changes. To reduce the complexity of a dynamic network and find the optimal path for the nodes, shortest path algorithm is applied as shown in Figure 28. Figure 28: Network formation

66 54 To better understand the signal flow, the Unified Modeling Language (UML) diagram for the signals between the nodes is shown in Figure 29. The calculation in GSA is based on the summation of all these nodes and the neighboring nodes multiplied with the number of signals exchanged between the nodes. Figure 29: UML for Path formation The flow of the Algorithm is shown in the next section. The Path Route model is a part of the communication model implemented in the Algorithm to set the roles of the nodes.

67 Algorithm Flowchart The flow of the Algorithm is as shown in Figure 30. The initial step consists of the SoC selection and modelling the parameters associated with it for the algorithm. In the work presented, Nordic s NRF51 SoC is used and the device parameters are set for the algorithm. Figure 30: Flowchart of the algorithm Each time a new device is added to the piconet, a singular value is assigned to the node through the VADF and the structure is thus updated. The algorithm keeps updating and is dynamic in nature.

68 56 The next step involves the formation of the node topology as shown in the example explained in the previous section. After the check for a connected graph, since it is a piconet and the nodes need a formation, it checks for the shortest path between the nodes. Once the neighboring nodes are traversed and the distance between them is calculated the initial step of the algorithm is completed. The next consists of the communication model, used for the link formation between the nodes. These links are dependent on the VADF generated during the initial scan of the network and is updated in this phase in case of any change. The last step consists of the network time usage that is used to check for longevity of the algorithm in terms of the implementation. The next section describes the algorithm in detail as implemented in this thesis and explains the ANCS as well. Limitation of Reference Algorithm The major limitation for this algorithm lies in the process of choosing a piconet Master, which relies on random assigning of the device ids. The identifier is either random or derived from the MAC address to maintain the uniqueness. This might not be suitable for heterogeneous devices. In addition, the network lifetime is limited due to a randomly chosen master as the duties of master include the routing of the packets through the slaves, establishment of the sleep interval, and checks on the signals sent. The random selection might not result in the optimal use of the node.

69 57 Algorithm Let the Root Node be R and the links formed between a Master (M) and a Slave (S) be denoted by // k be number of slaves in a given piconet Where M and S are linked (covered) through the subroutine L Lk Є M S Once these links are setup, the piconet formation is scanned through to implement the Roleswitching approach. //Scanning the piconet tree T (M, Sk) The initial check for shortest path algorithm, R Є M LMS R //Retaining the roles of the Nodes Hash-table (H) to retain the roles of all the nodes in the piconet through Value Assignment and Database Formation (VADF), H (P, Q) The feedback (F) of the nodes based on the energy needs to be transferred to the Links and the Route needs to be updated. F L (H, T) // Finding the shortest path to the root for optimization leads to reducing the node for (M, S) Є F F F U LMS end

70 58 where, LMS = the links from the Master to the Slaves // G the number of nodes to be put on the stack i.e. the Hash-table (H) be G output Gk = F The output of this algorithm (Gk) tell us that the piconet structure, is utilizing the best route from the root, here the Master node while creating the VADF for efficient power use. For a connection to be established between a BLE device and a smartphone, a valid connection method needs to be established for the devices to exchange information and access the Logical layer for data transmission. The method implemented in this thesis access the connection through ANCS approach as described in the next section.

71 Apple Notification Centre Services (ANCS) To access the various notifications that are generated on the BLE ios devices, Apple developed a convenient way, through Apple Notification Center Services (ANCS) [26], so that the bluetooth accessories could connect to the ios devices through a low-energy link [14]. Bluetooth Low Energy devices are identified with a UUID. Here, ANCS has a similar service UUID [26], UUID for ANCS: 7905F431-B5CE-4E99-A40F-4B1E122D00D0 [26] To access the notifications on the smartphone, there needs to be a method implemented on the SoC as explained in the literature review. So far, there aren t any specific methods implemented to talk to the notifications drawer on a smartphone. Figure 31 below shows the implementation flow for the SoC and ANCS implemented through the algorithm in this thesis. Figure 31: Implementation Flow The research here uses the NRF51 chip which has the algorithm embedded in it as well as acts as a BLE watch to communicate with the ios device. The piconet showed here can be scaled up to form a scatternet with an intermediatory chip talking to all the devices in the scatternet to form a database and dynamically be able to update the database values based on the nodes. This research

72 60 uses the example of BLE Watch device for accessing the notifications and performing different actions on these notifications using the GPIO pins on the NRF51 Module as shown in Figure 31. The ANCS Service, here residing in an ios device, is referred to as Notification Provider (NP). Any client requesting data from the NP, here any bluetooth accessory, is referred to as the Notifications Consumer (NC). ANCS is a service, which identifies a Notifications Consumer (NC) and a Notification Provider (NP) [26]. Figure 32: The lifetime of an ios notification [26] NP can have only one instance of ANCS Service. ANCS may not always be present in a BLE device given the nature of ios. Therefore, in order to observe the potential publishing (having an instance of the ANCS) and un-publishing of ANCS Service, the NC must find and subscribe to any service that is changed on the GATT service [26]. The lifetime of the notification is as shown in Figure 32.

73 Components of ANCS [26] I. Notification Sources The NC Notification Source types are as follows: i. Arrival of a new ios notification on NP ii. iii. Modification of an ios notification on NP Removal of an ios notification on NP As soon as the NC subscribes to the Notification Source characteristic, a GATT notification may be delivered. Therefore, it is necessary for the NC to be ready to properly accept and process the messages before it can subscribe to the type of notification source. II. Control Point and Data Source To interact with the ios notification, the NC uses this characteristic. NC may read the contents of a particular ios notification or perform actions on an ios notification or retrieve more information about the notification. Control Point and Data Source characteristics are used for the retrieval of these attributes. NC can issue a request to retrieve more information about any notification by writing specific commands on the control point of the ANCS. This is implemented through an object termed handler which talks to the NP via the GATT profile. The handler gets this additional information on any notification from the Data source characteristic if proper address is specified and the write is successful on the control point. By writing specific commands to the Control Point characteristic the NC can perform pre-determined actions on ios notification [26].

74 ANCS Code Implemented The code implemented for the GSA with different attributes and ANCS are highlighted below. The primary goal when accessing the ANCS is to obtain its UUID number [26]. The first step is accessing and registering that for a given ios device to communicate effectively with the BLE device. //UUID Check for ANCS {UUID = data [i + 4] + (data [i + 5] << 8); ble_trace ("%04 %04x uuid: %04x", Slave_handler, Master_handler, uuid); The next step is to access the GATT Profiles for them so as to communicate effectively with the ios device and get the proper attributes needed for the application. The third step is implementing the Handlers for Master and Slaves for the connection being established and then accessing the notifications on the ios device. //Check for GATT Service {Gatt_Slave_handler = Slave_handler; Gatt_Master_handler = Master_handler ;} //ANCS Service Implemented {ble_trace ("\r%04x e: %04x uuid", Slave_handler, Master_handler); ble_trace ((char *) &data [i + 4], 16); if (BT_MEMCMP (&data [i + 4], ANCS_SERVICE, 16) == 0) {ANCS_Slave_handler = Slave_handler; ANCS_Master_handler = Master_handler ;}

75 63 Once the ANCS handlers for Master and Slave are initialized, the issue turns to the other major problem of accessing these notifications and being able to perform actions based on these notifications. The code snippet implemented with the Tag shows a glimpse of the attribute profile to be accessed and the different commands used to access those. // ANCS Attribute Handling void ancs_attributes_command (UINT32 UUID_uid) {UINT8 access_notfn [20]; UINT8 *M_ access_notfn = & access_notfn [5]; access_notfn [0] = ANCS_COMMAND_ID_GET_NOTFN_ATTRIBUTES; access_notfn [1] = UUID_uid & 0xff; access_notfn [2] = (UUID_uid >> 8) & 0xff; access_notfn [3] = (UUID_uid >> 16) & 0xff; access_notfn [4] = (UUID_uid >> 24) & 0xff; * M_ access_ notfn ++ = ancs_client_notification_attr [ancs_client_notfn_attr_in]; * M_ access_notif ++ = (ancs_client_notfn_attr_length [ancs_client_notfn_attr_in] >> 8) & 0xff; bleprofile_sendwritereq (ancs_client.control_point_handler, access_notfn); The code snippet here presents a novel way of accessing the notifications from an ios device and then accessing the BLE profiles on the device interacting with it. To implement these notifications and profiles, a detailed database was created, first to initialize all the profiles and then to access them in different configurations based on the structure of the nodes. This presents a unique way to not only define the tree topology but also access the notifications on an ios device with a BLE device and in turn save power to better operate a BLE enabled device.

76 ANCS Test Conditions To remotely control a BLE based device, it needs to be connected to a smartphone. This research uses a smartphone which supports Bluetooth low energy protocol i.e. iphone 6 [26]. From Bluetooth low energy protocol [1] that there are several procedures, which are used to build a connection. Consider that there are two devices, device A (smartphone) and device B (BLE enabled device), the connection has the following steps: Connection: i. Device A broadcasts advertisement periodically. ii. Device B scans these broadcast channels, and waits for the advertisement from Device A. After the advertisement has been received, Device B will send a scan request to Device A. iii. When Device B has received, scan response from Device A, it sends a connection request to Device A. iv. After Device B has received the connection response from Device A, a connection between Device A and Device B is established successfully. Since Bluetooth low energy is more and more popular, its applications have been used in most of smartphones. One of these applications is getting notifications on any BLE based device, e.g. headphone, hearing aid or a smartwatch, controlling a phone call coming in through a phone directly from a headphone or a smartwatch.

77 Controlling a notification When both devices, device A and device B, are powered up, the smartphone broadcasts the advertisements. The BLE Enabled device, here the NRF51 SoC, scans the advertising channel and can get a scanning response from the smartphone as shown in Figure 33. Figure 33: Scanning UML The event sequence is as follows: 1. The smartphone broadcasts their advertisements through its advertising channels. 2. The NRF51 SoC starts scanning at advertisement channel. 3. The smartphone receives the scanning response from NRF51 SoC. After receiving the connecting response from the device, the connection procedure is finished. This process is shown in Figure 34. Figure 34: Connection UML

78 Getting the address This process is used so that the smartphone is aware of the device it s connected to. It also gives the smartphone access to control the devices that are in turn connected to the BLE enabled device e.g. lights in a smart home controlled through the smartphone. The process is related to the GATT layer, which is a layer used for data exchanging as shown in Figure 35. Figure 35: Getting address UML Data transmission To control the notifications on the smartphone, the device needs to send commands to the smartphone in the connecting event window. The event window and the category of the notification that is being sent to the BLE-enabled device determines the actions performed as shown in Figure 36. Figure 36: Data Transmission UML The conditions for successfully controlling the notification, getting the right address and being able to transmit data on that address, mark the success of accessing the ANCS. In the next section, the Hardware and Software used in this thesis are explained and the reason for their choice.

79 Hardware and Software Nordic Semiconductor s NRF51 Development Kit The Hardware used for the implementation of the proposed idea consisted of a Nordic Semiconductor s NRF51 chip as shown in the Figure 37. The chip contains system-level series devices consisting of clock control, interrupt system, Programmable Peripheral Interconnect (PPI), power and reset, watchdog and GPIO. The device address space instantiates system blocks for register interface and interrupt vector. All these instances are with their ID and base address are present in the datasheet of this chip [27]. The NRF51822 is low power 2.4 GHz wireless System on Chip (SoC) integrating 2.4 GHz transceiver, analog and digital peripherals, a 32 bit ARM CortexTM-M0 CPU and flash memory. NRF51 supports Bluetooth low energy and a range of proprietary 2.4 GHz protocols [1] [27]. Figure 37: Nordic s NRF51 Module There are various peripherals on NRF51 SoC along with GPIO Pins and the ADC needed for the work in this thesis.

80 Miscellaneous Hardware To measure the power consumptions in the chip during transmissions of signals, while connecting to other peripherals and at Idle, a power out connector for the chip was made. After the initial pinout of the USB Pin layout, a connector, with Vcc and Ground configurations, was made to get DC Voltage to be applied to the chip and then power was monitored on the Tektronics Digital Oscilloscope Software The Software s used in this thesis consist of Eclipse s integrated development environment and Bluetooth Analyzer Tool for simulations along with OmniGraffle for UML diagrams Eclipse Eclipse is widely used in integrated development environment (IDE) for computer programming. It consists of plug-in systems for customizing the environment apart from the workspace. This thesis uses C and C++ programming for the Nordic Semiconductors NRF51 chip. The development environment used for this thesis is Eclipse CDT for C/C++.

81 OmniGraffle OmniGraffle software has a graphical interface that allows enables communication through features consisting of several design tools, along with notes and drag and drop, What You See Is What You Get (WYSIWYG) interface that helps the user in creating prototypes and mockups easily as shown in Figure 38. It s similar to Microsoft Visio and differs only in features and use. While OmniGraffle can produce a wide array of graphics and visuals, it's used as a tool to create wire frames, Unified Modelling Language (UML) diagrams and the Sequence Diagrams. Figure 38: OmniGraffle GUI The UML s in thesis along with all the signals and communication events are created through OmniGraffle.

82 Signal Analysis tools Nordic s Sniffer and BLE Sniffer Software Bluetooth Smart communication between two Nordic devices can be viewed with Nordic s Sniffer. The Nordic NRF Sniffer is an application for the NRF51 Series used to view Bluetooth Smart communication between different interconnected devices. The major use of NRF Sniffer is to analyze different signals events exchanged between the devices. Nordic s Sniffer is a used in this research work as it helps in analyzing the behavior of the system once the configurations are changed. Accessing the Sniffer is as shown in Figure 39. Figure 39: BLE Sniffer The BLE Sniffer works with a Wireshark application, an open-source, free protocol analyzer, to examine the communication traffic and different events and their device sequences. It also provides near real-time display of BLE packets and identification of wireless events. The signals captured can be saved for later analysis and simulation if needed. Different components are required to analyze the communication traffic and events between devices.

83 Wireshark Wireshark is a network protocol analyzer. It acts as a sniffer tool paired with BLE Sniffer in this thesis to analyze over the air signals exchanged between the BLE devices. The Graphical User Interface (GUI) for Wireshark is shown in the Figure 40. Figure 40: Wireshark s GUI

84 72 The GUI contains different sections as shown in Figure 40, where an action can be chosen based on the application. The highlighted section in green in the figure shows the interface its sniffing, and as can be seen btle, which is Bluetooth Low Energy. This tool allows us to get into the data on events that are exchanged between the devices and is helpful for. The software not only shows the signals but also facilitates analysis with graphs and real time plots.

85 NRFgo Studio Nordic Semiconductor has designed a tool for setting certain values and modifying it along with the access to the bootloader on the chip. The tool is known as the NRFgo Studio. To access the different parameters and change the settings to analyze the FSM Model designed, the NRFgo Studio is used in this thesis. Figure 41: NRFgo Studio GUI

86 74 The tool outlines various sections as can be seen in Figure 41, which were used while accessing the different parameters on the NRF51 SoC and to burn the Bootloader files. The behavior of the system was analyzed through Wireshark to find the optimal settings for the model proposed in the research.

87 75 Chapter 5. Results of the Proposed Method The research in this thesis as described in the previous chapters is focused towards Bluetooth Low Energy devices and the power consumption on these devices. In this thesis, the design of the proposed Getaway Sink Algorithm is based on the shortest path algorithm to create a structural database for state retention. The database is further used as a singular variable table for roleswitching of the nodes in order to achieve better power consumption. In Chapter 4 a detailed analysis of the FSM Model and the Gateway Sink algorithm were presented and in this chapter the hardware setup, the simulations and the results of this proposed method are discussed. Figure 42: Experimental Setup The hardware platform is based on NRF51 chip which is shown in the Figure 42 below connected to a power supply and an oscilloscope to monitor the change in signals during communication. To supply power to the chip and monitor at the same time, a USB connector was configured to connect to the Power supply and the USB port in the chip. After the initial connections of the chip, an oscilloscope was connected to monitor the signals.

88 Signal Setup Experiments in this thesis were implemented through Nordic s NRFgo Studio and the power was measured through a custom arrangement of components and an oscilloscope to analyze the events. The algorithm runs an initial scan through the NRF51 chip before assigning the roles, to initialize the structure. After the initial scan, a pseudo network structure is generated for the formation and singular values are assigned to all the nodes in the event, forming a database. The scanning operation is detailed below. 1. Scanning Mode Once the chip is programmed and running, it will start scanning for devices. The scanning allows the devices to connect and the initial scan runs after the devices are connected to form the structure. The connection events for the chip shows the advertising packets sent over. The time required by the advertising packets determine the sleeping time for the chip and the results show better power consumption for longer sleep times. The pulses in Fig. 43 depicts several advertising packets. Figure 43: Pulse depicting scanning mode events

89 77 2. Connection Mode Once the chip is in the scanning mode, it finds a device in, then starts communicating with the device. The device which takes the role of the Master is the one trying to establish a connection with the chip, it will start the connection process. Figure 44 shows the connection event signals for the NRF51 chip. The time interval between the signals is the sleeping time where the device waits in order for other devices to connect. This thesis further describes detail of handling these parameters and presents the calculations for the implemented method. The narrower pulses depict connection events shown in Fig. 44. Figure 44: Connection Mode Events

90 78 Figure 45: Chip in Connection Mode Figure 45 shows the connection event and the acknowledgment signals sent between the NRF51 and the smartphone. The connection mode is the initial step, once it is setup, the algorithm kicks to scan through the network structure. The connection mode is the primary focus of research in this thesis.

91 Packets Analyzed Throughout this thesis, the following terms are used for communication of different signals utilized between a Master and a Slave. Before forming a connection, the initiator is scanning for a connection and hence known as a Scanner and the device that advertises is known as the Advertiser. The Scanner enables the radio to form a connection periodically which is determined by Scan Window and Scan Interval. Figure 46: Advertising Event for NRF51 SoC [27] Advertising: Figure 46 shows an advertising event and the breakdown of the event in time. It stays in Sleep unless there is a need to pair with a device. Once it wakes up, it starts advertising with initial information and starts listening to any responses. The terms introduced and used throughout this thesis comprises of the following: startadv is for broadcasting of the device with its name and Universally Unique ID (UUID). startadvack is the response received to the Microcontroller once the device starts advertising. stopadv is used to stop advertising of the device. AdvCharacteristicNotif is used for sending the characteristic information on successful response from the device it is communicating with.

92 80 SendRespn For a read/write request to the device communicating with a device needing an acknowledgment of the command being executed is used to exit the GATT Server. The devices in search of pairing with other devices are called the Initiators. The transition to a Connection State, from an Advertising State, initiates once the device advertising accepts the Connection request from the device it wants to be paired with. The Initiator takes the role of a Master once the Connection between the devices is established and the Advertiser becomes the Slave. This is termed as a piconet formation. Figure 47: BLE Device transmitting ADV Packets Figure 47 shows the signals extracted on the NRF51 chip through the NRFGo Studio. The simulation is configured through the NRFgo Studio and the data packets are sniffed through Wireshark. These signals are the advertising events once the chip is ready to establish a connection. NRFgo allows us to extract these signals once it is setup.

93 81 The Advertising events captured at different intervals through the sniffer are as shown in Figure 48. The time interval between the events was setup in the NRFgo Studio while programming the NRF51 module. Figure 48: ADV Packets for NRF51 SoC [27] The Master in an event determines the frequency hopping scheme that the Slave follows during that connection. When the connection is established, the Master sets a synchronization time known as the Hop Interval. The Hopping pattern used is based on the 37 frequencies of the ISM Band. The structural hierarchy consists of the physical layer, the Logical layer and the Logical Link Control and Adaptation Protocol (L2CAP) channel for the device. All the layers have links connecting them to the other layers. A physical link is formed between a Master and the Slave in the physical layer but there are no physical links between two or more Slaves. However, more than one link is permitted for a slave to connect to multiple Masters in another piconets.

94 82 The piconet is setup according to the GS algorithm, where initially the nodes are put on VADF based on singular values assigned to them w.r.t to the shortest path from the root node. Figure 49 shows the advertising packets sent by NRF51 chip before connecting to any device captured by the Sniffer in Wireshark. The Packets are transmitted at regular intervals with a preset sleep time for the device, which allows the device to save power and then use the processing time based on the role-switching described in Chapter 4. Figure 49: ADV Packets on SoC captured by Wireshark and BLE Sniffer Once the Scanner initiates the connection and the connection is established between an advertiser and scanner, the device initiating the connection becomes the Master and the other the Slave. In the configuration used in the research, the Apple smartphone initially assumes the role of the Master and later through the use of Gateway Sink algorithm, the role is performed by NRF51 chip. Figure 50: Data packets exchanged between the devices

95 83 Figure 50 shows the connection event packets on the NRF51 chip extracted through the simulation. Once the scanning request is sent by the device, after finding the right advertising packets of the device it needs to connect with, a connection is established via the connection event. In the setup described above, the NRF51 becomes the slave initially to offer the services it has to the Apple smartphone via the Apple Notification Center Services (ANCS). The peak of the captured signals provides enough information to calculate the power consumed at every event that the devices are communicating and exchanging signals. Figure 51: Hopping Sequence triggered and Sniffer Initialized The Gateway Sink algorithm is implemented after this connection is established and signals with attribute and characteristic values are transmitted between the devices. These transmitted signals have different Attribute ID s and characteristic s which vary over the time taken for the communication and the length of the packet transmitted and received between the devices. The NRF51 Module sends a data handler to get the string to complete the exchange. The advertisement packets and the connection event packets are sniffed by the BLE sniffer. Figure 51 below shows the configuration of the sniffer implemented for the chip NRF51 and the hop sequence chosen for the sniffer.

96 84 The sniffer shows the devices in range, initializes and then starts sniffing the events exchanged between the device and the other connected devices in the piconet. Once the Sniffer is configured, the Wireshark network analyzer can be opened through the terminal window that is shown in Figure 52. Once the initial settings are configured, the tool can be used to monitor over the air packets sent between the devices. Advertising events along with the type of the protocol and the length of the packet as highlighted can be seen sniffed through the software to form a connection that are broadcasted by the NRF51 chip. Figure 52: Packets Sniffed between NRF51 SoC and Apple Smartphone The data here is the communication between the programmed chip and a smartphone to check the viability of information being exchanged and the power consumption with each transmitted or received signal.

97 85 The NRF51 initially transmits the advertising packets to setup a connection with a device. In this research, the Apple s smartphone is used as the device that forms a connection with the chip. Once the smartphone finds the advertising packets that it s looking for it send a SCAN_REQ as shown in figure 53 and forms a connection with the advertising device. The smartphone initiating the connection becomes the Master and the device advertising, in this case the chip becomes the slave in the formed piconet. Figure 53: Advertising Signal and Data sniffed on the Chip The bits highlighted in green in Figure 53 are used for debugging the transfer of each signal over the air and to analyze the code implemented in the NFR51chip.

98 86 The I/O graph representation of the signals exchanged between the Master and Slave is as shown in the highlighted section of Figure 54. The ADV_IND are the advertisements sent by the chip programmed to connect to the smartphone. Figure 54: I/O graph, Scanning Request and Response The SCAN_REQ are the signals transmitted by the smartphone to connect to the NRF51 Module that is been programmed to connect to the smartphone and then through Apple Notification Centre Services (ANCS) access the notifications. Once the SCAN_REQ is received by the NRF51 chip, it sends a SCAN_RSP which is a response to the request with the handles required for communication. Here, to establish a connection with the Application Layer and access the Data packets, a link is formed between the smartphone and the device this is designed and implemented on the chip through ANCS.

99 87 These exchange of responses are recorded along with the time taken for their exchange of acknowledgement signals to calculate the power consumption. The calculations are based on the time taken by these signals and the packet size of each event that takes place for devices to be connected. For example, from the highlighted section in figure 55 the time interval with reference to the first frame is 3.09 sec and the frame length is 32 bytes that s transmitted and received. Figure 55: Link Layer Indicator Signal The CONNECT_REQ establishes a connection and now the devices need to talk to the corresponding Link layers on other side in order to access each other features.

100 88 As seen in Figure 56, the initial information is exchanged between Master and the Slave with the signals LL_VERSION_IND. Figure 56: Link Layer Feature and Response Signals Once the SCAN_REQ and SCAN_RSP are exchanged between the devices, a CONNECT_REQ is sent over by the smartphone. The CONNECT_REQ in turn assigns the role of Master and the Slave to the device scanning and advertising, respectively. This forms a Bluetooth low energy connection and thus there is a need to define the GATT/GAP layers on the Bluetooth available on the NRF51 module. The NRF51 chip acts as a bridge for the piconet formed to run the algorithm.

101 89 In addition, we implement a novel way for the chip to behave as a watch communicating with the smartphone. Therefore, the NRF51 acts both as Piconet Bridge and as BLE watch device. The initial configurations are important to layout the network for any application that needs to talk to the smartphone and thus establish a bond. The signal LL_FEATURE_REQ and LL_FEATURE_RSP are followed after the LL_VERSION_IND to exchange the information of the profiles and descriptors available on the device. One of roles of the NRF51 chip is to run the Gateway Sink algorithm, once the initial connection is established and the CONNECT_REQ is routed to the watch part of the chip. The chip now plays two roles by the way its programmed through the algorithm. Hence, the initial role of the chip is implementing the Gateway Sink algorithm for the piconet and the second is to be able to communicate with the smartphone via the Apple Notification Center Services (ANCS). For instance, an LL_FEATURE_REQ is sent by the smartphone to the watch, as shown in the highlighted section in Figure 56 to get the information of the features that the Slave has to offer, e.g. for a thermometer this could be temperature and min/max functions. The Frame information in the bottom section of Figure 56 shows the value of the Frame length. The numbers, shown at the bottom, in the left column depict the data bytes being processed with the information that was passed by the algorithm to the VADF in order create a database of these values.

102 90 Figure 57 shows the Attribute signals that are successfully initialized once the Link layer is setup between the devices to gain access to the set of characteristics. This confirms the communication between the smartphone and the chip now acting as a watch. The slave through the descriptor parameter relays back the attribute information to the handler of the Master, also used by the VADF. These values are further utilized in the algorithm for the retention of the attribute profiles once the connection is formed and the Master needs to know any information on the Slave device. Figure 57: Attribute Request and Response Signals The handling of signals through the Link layer on the devices involves a method for gaining the access to the GATT layer. GATT layer is responsible for all the communication between the Master and Slave in a piconet.

103 91 The Generic Attribute (GATT) Layer is the layer that needs to be setup for the access to different profiles on the device that Master needs after connection. An example of this could be accessing the temperature variables on a BLE-based thermometer. The device connecting to it might need information about the units for temperature measurements. The profiles for such applications are accessed through the GATT layer. The approach implemented in this thesis to setup the layers and gain access to all these profiles and characteristics is done through an approach of recursive formation of links and the retention of the states with an improved use of handlers to communicate between devices. Figure 58: GATT Request and Response Signals Figure 58 shows the handles used by the algorithm to setup the GATT layer. These handles are dynamic in nature and are used recursively in the code to manage the parameters. This method gives the user the portability of setting up the GATT layer on different variants by tweaking the code to the right formation and gaining access to the profiles that are available on the BLE device.

104 92 Once the access to the GATT is achieved, communication packets transmitted between the Master and Slave needs to be analyzed. The communication packets per event against time is as shown in the Figure 59. The packets usually stay in the range of 5-10 packets/event while scanning interval although while exchanging information can go between packets/event. Figure 59: Packets/event against time The variation of the packet size is shown in Figure 60 which depicts the behavior of the chip with the implemented algorithm and its reaction to the packets sent over the air while forming a bond with another BLE device. This exchange of information contains bytes in the packets sent over; hence, decoding these signals with a transmission of acknowledgement signal, takes up radio activity both on the receiving and transmitting side of the communication link. Figure 60: Variation of Packets/event obtained from Wireshark

105 93 BLE devices are prone to wait for these packets, utilizing vital power on the chip; hence, power efficiency is improved by minimizing the transmission error of each. The bytes transmitted and received by the BLE devices in this simulation trace a graph as shown in Figure 61. This plot highlights the radio activity while forming the connection between the NRF51 chip and the smartphone. The bytes transmitted and received affect the connection interval as well as the integrity of the signal and information exchanged between devices. Figure 61: Bytes/event against time The bytes transmitted during an event are shown with red arrows, and the activity during the Sniff mode is shown with the green arrows in Figure 61. Transmitted bytes in terms of packets are used in the calculations in this thesis to further analyze power consumption through the proposed algorithm. As can be seen, the activity during Sniff mode is reduced to more than 50% and the residual activity is on the algorithm side of the NRF51 chip to manage the smartphone and the watch implemented on the same chip. This entails checking to see if the bits are exchanged in the right order of the role changing assigned by the VADF. The proposed method keeps the radio activity to a minimum while the number of bytes stay in the threshold of 25 bytes.

106 94 Figure 62 shows the signals extracted on the NRF51 Module and the parameters that will be used in the next section to calculate the consumption of power during different modes of the chip. Since the chip has the algorithm embedded and also acts as a watch, the power consumption on the chip is measured as a whole. It can be shown from the calculations that even though the chip performs multiple functions at a given time the consumption of power is reduced substantially and can be implemented for a scatternet. Figure 62: Variation of Bytes/event All these exchanges of signals play an integral part of setting up a mechanism for communication between devices. The novel method developed in this thesis allows an efficient approach of handling and acknowledging these signals. The proposed method could be applied to different makers of smartphones; hence making it a universal choice for BLE communication and performing actions. In the next section, the setup of NRF51 chip is shown and the calculations are performed for the power consumption on the chip during different modes of operation.

107 Protocol Layer Connections The Protocol stack plays a major role in transmitting and receiving the bits transferred during the communication. The Unified Modeling Language (UML) diagram in Figure 63 shows the different connection at various levels and then explains the Protocol Stack and the architecture implemented in this thesis. Figure 63: Connections UML Figure 63 shows the connections exchanged between devices. Once they are connected, it involves accessing and talking to the Generic Attributes (GATT) and Generic Access Protocol (GAP) over

108 96 the BLE link being established between the devices. The GATT is located just above the Controller layer and below the Application Layer in the Protocol Stack of the BLE. The roles of low energy devices are defined in the GAP layer of the stack and the profiles in the GATT layer. These profiles are then structured accordingly to support the profiles with a set of data and services. As shown in Figure 64, the Protocol Data Unit (PDU) [1] is illustrated as used in the Bluetooth Low Energy technology. The transfer on the number of bits is a vital parameter for the energy utilized by the device and the Payload that is being transmitted. Figure 64: Protocol Data Unit (PDU) [1] Where, Preamble: 1 Byte, Access Address: 4 Bytes PDU: 39 Bytes CRC: 3 Bytes Header: 1 Byte, Advertiser Address: 6 Bytes, Payload Length: 1 Byte Payload: Bytes Total Length: 47 Bytes Therefore, the total length of the PDU sums to 47 bytes and 31 bytes are used for the payload.

109 Event Analysis on the Chip To check the power savings, we now present the real time signals exchanged between the Master and the slaves of the piconet formed between the Apple smartphone, the NRF51 chip implemented through the Gateway Sink Algorithm and its associated watch. The next sections present power calculations for scanning and connection modes Chip in Scanning Mode The analysis for the scanning mode before and after the implementation of the algorithm is presented below. Figure 65 shows the signals transmitted by the chip while in the Scanning Mode and the Peak to peak voltage before the implementation of the proposed algorithm. Notice that the sleep time, tsleep (time between the peaks) is approximately 32 ms. The time interval shown in the Figure 65 is used to calculate the duty cycle between the acknowledgment signals exchanged between the devices. Figure 65: Chip in Scanning Mode at 154 mv RMS before the algorithm

110 98 Now for the events within the acknowledgments received, as highlighted in Figure 65, the time interval where the chip stays active is for the 3 events between the acknowledgment signals with one of them staying active for a longer period of time. As these events are minutely placed, for calculations each event is considered as 1 ms interval. Therefore, from the Figure 65 we get that the chip stays active for approximately 4 ms with the total time approximately 96 ms, which gives us t1/t = 4/96 = For the CR2032 battery cell [28], Average current = 240 mah To compare the results with and without the proposed modification, assume the average runtime of a single CR2032 battery [29] to power the chip be 1 year which is 8760 Hours. Therefore, current drawn = 240 mah 8760 h For an impulse waveform, from [30] we get, = ma 13 Vpk = VRMS / T/t1 and Vavg = Vpk t1 T 14 Vavg= 1 Vpp * = V Therefore, the power consumed by NRF51 Tag = V * ma = 5.51 µw

111 99 After the implementation of the proposed algorithm, the sleep time for the device is considerably increased as shown in Figure 66. Figure 66: Chip in Scanning Mode at 115 mv RMS with the proposed algorithm Now for the events within the acknowledgment events are as highlighted in Figure 66, the time interval where the chip stays active is for the 3 events between the acknowledgment signals. Therefore, from the Figure 65 we get that the chip stays active for approximately 3 ms, with the total time approximately 150 ms, this time is used to provide fair comparison with the previous calculation. Based on the above, the calculations are as follows: t1/t = 3/150 = 0.02 From Equation 13, For the CR2032 battery cell, current Drawn = = ma From Equation 14 Vavg = V * = V

112 100 Therefore, the power consumed NRF51 SoC = V * ma = 3.63 µw, A reduction of % is achieved as compared to without the role switching algorithm as shown in Figure 65 for the scanning mode. The power consumption shown here addresses the scanning mode and the next calculations show the power reduction for connection modes. Based on the implemented algorithm, the power consumption should considerably be reduced in the connection mode as fewer acknowledgements are transmitted and longer sleep times are achieved.

113 Chip in Connection Mode The analysis for the connection mode before and after the implementation of the algorithm is presented below. Figure 67 shows the connection event and the sleep time before the algorithm is implemented. Figure 67: Chip in Connection Mode at 428 mv RMS before the algorithm From Equation 13, For the CR2032 battery cell, Current Drawn = = ma In the connection mode, from Figure 67, the connection event is shown where the time interval when the chip stays active is longer. The power consumed by the chip here is calculated with two components, the connection event power and the acknowledgment event power for total of 220 ms interval as shown in Figure 67. The reason for doing this is because there is an almost constant

114 102 voltage (about 220 mv) within the connection interval (as shown in Fig. 67). There are some few spikes, but the constant voltage level is the dominant component in the connection event. For the connection event, the chip stays active for 105 ms, t1/t = 105/220 = From Equation 14, Vavg_connection_1 = * = V Pc1 = * ma = µw For the acknowledgement event, the chip stays active during five peaks shown in Fig. 67, with each peak as assumed before is 1 ms, for a total of 5 ms. Therefore: t1/t = 5/220 = From Equation 14, Vavg_acknowledgement_1 = 1.53 * = V Pa1 = * ma = 6.2 µw The total power consumed, Pt = Pc1 + Pa1 = µw

115 103 After the algorithm implementation, for the connection mode, longer sleep can be seen in Figure 68. It also shows the connection event that last a little longer than one see in Figure 67, due to the algorithm activity on the chip. Total Time Figure 68: Chip in Connection Mode at 314 mv RMS with the proposed algorithm For the connection mode, the events within the acknowledgment events are as highlighted in Figure 68. Before the acknowledgment signal is received by the chip, it is constantly active and the connection event is longer due to the activity of the chip and then the algorithm that is executed through the chip. The power consumed by the chip here is also calculated with two components, the connection event power and the acknowledgment event power for total of 240 ms interval as shown in Figure 68. From Equation 13, for the CR2032 battery cell, Current Drawn = = ma