Silvia Capone, Riccardo Brama, Fabio Ricciato, Gennaro Boggia and Angelo Malvasi

Transcription

1 White Paper Enhancing Energy Efficiency of IEEE e DSME: Modeling and Simulation Silvia Capone, Riccardo Brama, Fabio Ricciato, Gennaro Boggia and Angelo Malvasi COPYRIGHT 2014 CMC LABS, PRINTED IN ITALY. ALL RIGHTS ARE RESERVED. CMC Labs - A division of CMC S.r.l. - Contrada Pagliarulo SN Carovigno, Italy - Ph Fax info@cmclabs.com

2 Abstract Wireless sensor networks are drawing much attention as an effective means to enable the Internet of Things. In this context, energy efficiency is an important requirement in applications where battery-powered sensing devices are exploited. Battery power saving can be addressed using many techniques, concerning different layers of the OSI model. This work addresses energy consumption in MAC protocols from a transceiver usage perspective. We first describe a set of protocols that includes IEEE and IEEE e DSME. Then, we analyze their energy consumption and propose a set of Enhancements for Low-Power Instrumentation DSME Applications. Finally, given a wireless network topology, we compare the performance of the above mentioned protocols by simulations. Obtained results show that, for end devices, the proposed approach allows an energy consumption reduction up to a factor of 9 with respect to the IEEE , while enabling for higher throughput, and up to a factor of 7 with regard to native IEEE e DSME.

3 1 Introduction Wireless Sensor Networks (WSNs) allow to gather a huge range of information enabling a thorough and continuous monitoring of both indoor and outdoor areas. Since wireless sensors could be spread on the field, or located in very hard to reach positions, researchers focused particular attention on developing energy-efficient communication protocols to extend their lifetime avoiding unnecessary maintenance. Low-power Personal Area Networks (PANs) have been addressed by IEEE standard [1]; the last edition of this standard, i.e. IEEE [2], supports a variety of physical specifications allowing its adoption virtually in every application. Recently, the introduction of the IEEE e-2012 amendment has enhanced the Medium Access Control (MAC) functionalities in order to support the industrial market [3]. Three different MAC operation modes are supported: Deterministic and Synchronous Multi-channel Extension (DSME), Time Slotted Channel Hopping (TSCH), and Low Latency Deterministic Network (LLDN). The main advantage of improved version of the IEEE is to overcome limitations of the standard protocol for industrial applications, especially with regard to real-time operation, throughput and reliability [4], [5]. In particular way, DSME approach is attractive due to its flexibility, enabling trading latency, throughput, and efficiency as needed by application. Time synchronization, in this case, is realized by means of broadcast beacons, allowing each device to keep track and correct clock drifts. Moreover, by using frequency multiplexing, DSME increases throughput making this approach suitable for cluster-tree, multi-hop sensor networks [6] and it also enhances WSN reliability under WLAN interference [7]. Designing network solutions for industrial market, it is quite usual to deal with applications where the network traffic is destination-oriented [8]. Measurements, collected by remote wireless sensors, need to be harvested by a single device behaving as a Wireless Network Access Point (WNAP). Wireless sensors are usually battery-powered and could be installed in harsh environments not easily accessible; WNAPs are mains-powered, thus are not necessarily power constrained. In all these applications prolonged lifetimes, straightforward installation and reliability are the paramount challenges. Despite DSME seems the most suitable MAC in such scenarios, it still lacks of solutions optimizing its power consumption. In this paper we propose a method called Enhancements for Low-Power Instrumentation DSME Applications (ELPIDA). While keeping main features of IEEE e DSME MAC protocol, i.e. bounded delay, high throughput, scalability and standard compliancy too, this approach shows an improvement of power consumption without introducing extra overhead or long latency. The unique request to enable ELPIDA low-power strategies is that every frame needs to be always acknowledged by receiver through proper ACK frames. The proposed approach aims to rationalize network power consumption, minimizing it for wireless sensors (where energy availability is poor) and shifting it towards WNAPs. We will show that in cluster-tree networks, where traffic is generated by end devices and directed towards a single sink, power consumption of end devices can be dramatically decreased by means ELPIDA method, keeping high the network reliability. ELPIDA has been implemented 1 and evaluated by means of OPNET simulations. This paper is organized as follows: in Sec.2 we detail IEEE and DSME protocols as a background for Sec.3 in which we present the proposed ELPIDA. Sec.4 reports measured energy profile of CC2520 transceiver. In Sec.5 we introduce the simulation scenario and analyze results comparing ELPIDA with the other two standard protocols. Conclusions follow in Sec.6. 1 OPNET models for both IEEE e DSME and ELPIDA protocols are available at 1

4 2 Protocol Overview 2.1 IEEE IEEE [2] is one of the most widely adopted point-to-point communication standards for Low-Rate Wireless PANs (LR-WPANs) [9]. Its success lies in the design of a protocol stack comprising a physical layer (PHY) and a MAC developed for low-cost, low-power, and resource-constrained wireless devices. In beacon-enabled mode, the PAN coordinator sends a beacon frame each Beacon Interval (BI). This allows the identification of the PAN, the synchronization of associated devices, and the description of the superframe (SF) structure. Each BI is comprised of an active and, optionally, an inactive period defined by two parameters: the Beacon Order (BO) and the Superframe Order (SO). The SF, shown in Fig. 1, consists of 16 time slots of equal duration. Beacons are transmitted during the first time slot, whereas remaining slots are used for network traffic. Right after the beacon slot, a Contention Access Period (CAP) begins; during it channel is accessed by a Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) algorithm. The length of the CAP is basically 15 time slots, but it can be shrunk on demand up to 8 time slots, thus forming a Contention Free Period (CFP) whose length cannot exceed 7 time slots. During the CFP each time slot is reserved to a single device, avoiding the need for CSMA/CA. Reserved time slots are called Guaranteed Time Slots (GTSs) and form a set of Reserved Links (RLs) with given bandwidth, latency, and direction. A detailed description and analysis of the protocol is given in [10] and [11]. Figure 1: IEEE superframe structure. 2.2 NATIVE IEEE e DSME The IEEE e DSME MAC protocol [3] has been proposed mainly for multi-hop network scenarios. By exploiting both time and frequency multiplexing, it allows a very efficient allocation of available resources. Running only in beacon-enabled mode, it keeps devices synchronized by means of timing information embedded in periodic Enhanced Beacons. Channel access is based on a specific time structure called multi-superframe (multi-sf). Each multi-sf consists of a collection of SFs, very similar to those in [2]. However, unlike IEEE , the BI of a DSME-enabled PAN consists of multi-sfs with no inactive period, as shown in Fig. 2. CAP length is fixed to 8 time slots, which periodic network monitoring data traffic, urgent or non-periodic data can be sent in. During CAP, devices shall compete for channel access using slotted CSMA/CA. The remaining 7 slots are used for multi-channel DSME- Guaranteed Time Slots (DSME-GTSs), which can be used for Reserved Links establishment. These links represent a directed communication path between devices and are characterized by pair-wise assignments of channels and time slots realizing Upstream (US-RLs) or Downstream 2

5 Reserved Links (DS-RLs). The multi-sf structure is defined by the MultiSuperframe Order (MO), together with BO and SO. Maximum number of routing devices, including PAN coordinator, is given by the total number of SFs in the BI, corresponding with the available number of beacon slots. Figure 2: IEEE e DSME multi-superframe structure. DSME MAC introduces also a CAP reduction feature. When such a reduction is applied, all CAPs, except the one in the first SF of each multi-sf, are substituted with DSME-GTSs. This leads to a twofold result: a reduced power consumption and an increased bandwidth (or decreased latency). Power consumption can be reduced avoiding to turn ON receivers during suppressed CAPs; while multiplication of available DSME-GTSs allows PAN coordinator to either reserve more bandwidth or to allocate more nodes within the multi-sf. To enhance link reliability in harsh channel conditions, DSME MAC employs two types of channel diversity schemes: channel adaptation and channel hopping. In channel adaptation devices switch to another available frequency channel as soon as current link quality drops below a given threshold. In channel hopping mode, devices hop continuously through a predefined channel list regardless of link quality. Since DSME allows the allocation of RLs on different channels, the whole aggregate network throughput increases significantly, achieving an efficient support for high traffic loads. To assess its performance, we implemented a native IEEE e DSME simulation model starting from [12]. Analysis of the implemented protocol enables simulation based investigations of cluster-tree WSNs in beacon-enabled mode. 3 ELPIDA: Enhancements for Low-Power Instrumentation DSME Applications In wireless measurement systems, energy is a pressing challenge and, as we will see in Sec. 4, it is mainly spent during CAP in IEEE protocols. Usually, in fact, end devices are in receiving mode during CAP, waiting for frames eventually sent by PAN coordinator or routing devices. Unfortunately, in a destination-oriented data flow, CAP time is mostly unused because traffic is preferably generated during collision free US-RLs. In this paper we show that in cluster-tree topology, it is possible to dramatically decrease power consumption by means of appropriate solutions. We synthesized them in a novel proposal that we call Enhancements for Low-Power Instrumentation DSME Applications (ELP- IDA). Three main adjustments are introduced: (i) CAP Wake-up, (ii) DS-RL Wake-up, (iii) and Beacon Look-up. Proposed power saving features are easily triggered by a single field of standard packet header: the Frame Pending field. Therefore ELPIDA does not introduce any extra overhead in destination-oriented networks. In non cluster-tree topology, this approach needs overhead for peer-to-peer communications due to DSME-GTS mechanism but keeps an 3

6 improvement in end devices power consumption compared to standard MAC protocols detailed in Sec.2. Following description targets a multi-hop, destination-oriented, network scenario. In this scenario a single device acts as PAN coordinator and traffic sink, a set of devices act as routing devices, i.e. they are parents of child nodes, and a set of data originating end devices are present. We call US-RL the Reserved Link from a child device to a parent device, and DS-RL the one from a parent to a child. The large amount of available DSME-GTSs allows to permanently assign one US-RL and one DS-RL to each child. Each Reserved Link has an adaptive length and it can last up to 7 slots without CAP reduction or up to 15 slots if CAP reduction is ON. Frame generated in each direction must be always acknowledged by receiver through proper ACK frames. 3.1 CAP WAKE-UP In ELPIDA network scenario DS-RL and US-RL are necessarily negotiated during network formation. This allows critical end devices traffic (e.g., periodic monitoring, urgent or nonperiodic data) to be preferably sent in US-RLs. Moreover, since traffic is destination-oriented, it is unusual for parents to send frames to children. Thus, right after Reserved Link allocation, end devices are allowed to become lazy and to fall asleep during the whole CAP of parent s SF. Of course PAN coordinator and routing devices are not as lucky and should always stay in receiving (RX) mode during CAPs to allow network management traffic. If a parent needs to send broadcast frames to children, it can order a CAP Wake-up by using the Frame Pending field of the Enhanced Beacon frame. Since Enhanced Beacon frame is broadcast, a set Frame Pending field is received by every child, staying in RX mode during the next incoming CAP. 3.2 DS-RL WAKE-UP Despite DS-RLs are reserved during network formation, in order to ensure collision free links with known latency, end devices only rarely receive traffic. This is due to the destinationoriented behavior of proposed network scenario, mainly generating traffic directed towards the sink. Thus, to avoid wasting power, wireless sensors fall in sleep mode also during their own reserved DS-RL. If a parent needs to send unicast traffic to a child, it can act on another Frame Pending field: the one in ACK frame. A child receiving an ACK with Frame Pending set must activate its transceiver in RX mode during the following DS-RL. From this moment on, DS-RL will be listened until data frames with Frame Pending are received. Thus, parent devices need to receive frames in US-RL before being able to forward traffic in DS-RL, yielding a regular flow of US-RL traffic and associated ACKs during normal operations. In irregular situation (e.g., if one child node appears to be silent) the parent can still resort to CAP Wake-up to communicate with its child. 3.3 BEACON LOOK-UP Even if not directly addressed in this work, loss of synchronism is a further issue increasing end devices power demand. In DSME synchronism is enforced through beacon frames. In order to minimize RX time, wireless sensors turn their transceiver in RX state right before the beginning of a beacon slot. Unfortunately, low-cost devices, with poor crystals, are likely to be affected by significant clock jitter, leading to an increased chance to miss beacons. After amaxlostbeacons (by default set to 4) consecutively lost beacons, IEEE MAC declares the loss of 4

7 Figure 3: Robustness to synchronism problems. synchronism, leading to the so called Orphan State. Hence, either an Orphan Channel Scan or a new Association procedure are triggered [2]. Unfortunately both these procedures are quite power hungry. Beacon Look-up is a way to reduce the likelihood of loosing a beacon frame. This approach aims at linearly increasing end devices beacon frame reception window for each lost beacon interval, as shown in Fig. 3. Upon reaching amaxlostbeacons the ELPIDA behavior is still to declare loss of synchronism as in [2]. 4 Energy Model Energy is a major design driver in wireless sensor networks and is hence a major focus of this work. To increase results accuracy and to optimize the performance of energy critical nodes, simulations should include a real battery model. For this reason, we performed an experimental current consumption characterization of TI CC2520 transceiver, shown in Fig. 4. Designed to Figure 4: Experimental characterization of TI CC2520 current consumption profile. optimize performance both from usability and efficiency point of views, this device, implementing a IEEE fully compliant PHY, embeds also some useful MAC functions allowing using it with ultra low-power microcontrollers [13]. To decrease its power consumption, sleep mode features are implemented, leading to 5 functional states: sleep, idle, reception, synchronization, and transmission. Synchronization state refers to a transceiver in RX mode waiting for the beginning of a frame; interestingly its current consumption is higher than when actually receiving the frame itself. 5

8 Analyzing experimental transceiver characterization and described SF structure, it is possible to forecast power consumption simply considering the state in which transceivers are operating. Comparing Fig. 5 and Fig. 6 it can be shown that IEEE e DSME is likely to be characterized by a lower energy consumption than IEEE This is evidently due to a shorter CAP period in which transceivers are in RX state. By minimizing such a contribution, it is possible to dramatically reduce overall protocol power consumption. This result is achieved, as shown in the lower part of Fig. 6, by our proposed ELPIDA model. In ELPIDA, right after network formation (shown in the first SF), devices are allowed to fall in sleep mode during CAP, thus leading to current profiles clearly highlighting a decreased power consumption with respect to DSME. To verify this behavior in presence of real network traffic, a dedicated battery model has been realized basing on a finite state machine [14]. This allows computing energy consumption profiles that closely match (for both level and timing) experimental measurements presented in Fig. 4. A power consumption oriented comparison of the three MAC protocols is discussed in next section. Figure 5: State analysis of IEEE SF with transceiver current consumption. Figure 6: State analysis of native DSME and ELPIDA SF with transceiver current consumption. 6

9 5 Performance evaluation Several analytical and simulation models of IEEE protocol have been implemented. Many popular network simulators natively include a model for this standard. The one in OPNET Modeler [15] supports only non beacon-enabled mode, therefore, GTS mechanism cannot be simulated. Based on IEEE OPNET simulation model developed by IPP HURRAY! Research Group [16], we realized what is, as far as we know, the first ever proposed simulation model of IEEE e DSME MAC protocol. Then, ELPIDA enhancements have also been implemented allowing to compare the three protocols. 5.1 SIMULATION SCENARIO Simulations have been performed considering a statically deployed, cluster-tree WSN. Topology hierarchy is defined by parent-child relationships forming a directed tree. Implemented simulation model enables multi-hop communication by means of three types of nodes: PAN coordinator, router, and end device. In proposed topology, multi-hop communication is deterministic and each node forwards frames, on a periodic basis, only to its pre-defined parent. Messages are routed from cluster to cluster until reaching the PAN coordinator, acting as data sink. We assume both PAN coordinator and routers are mains powered, while end devices power source is an embedded, rechargeable battery. As shown in Fig. 7, the simulated network topology consists of one PAN coordinator (R 0 ), Figure 7: Network simulation topology. three router nodes (R i ) participating in multi-hop routing, and four end nodes (N i ) for each router. Unlike [12], in this work simulation attributes are dynamically set by MAC algorithm, while network ones are user defined. This allows an adaptive Reserved Link allocation and deallocation, therefore the number of required time slots is modulated according to node needs. Channel quality, on the other hand, contributes to the choice of channels paired with DSME-GTSs. In this simulation model also Channel Adaptation has been implemented. Tab. 1 summarizes simulation model main parameters, whereas in tab. 2 values for SF structure parameters are shown. As can be noted, we assume that devices need to synchronize maximum once per second, thus BO is set to 6; nevertheless all these parameters can be 7

10 Table 1: WPAN Simulation conditions Simulation duration 20 min Data packet length (payload) 100 bits Data packet traffic type Real-time (GTS only) ACK Enabled Max number of retransmissions 3 Bit-rate 250 kbps Frequency range GHz Number of Channels 16 Table 2: Superframe structure parameters BO Beacon Order 6 M O Multisuperframe Order 5 SO Superframe Order 3 BI Beacon interval ms M D Multi-Superframe Duration ms SD Superframe Duration ms Slot atimeslotduration 7.68 ms N 1 = 2 BO MO Multi-SF in BI 2 N 2 = 2 MO SO SF in multi-sf 4 modified according to network needs (e.g. density, traffic, and coverage). 5.2 SIMULATION RESULTS This work presents an energy efficient implementation of the IEEE e DSME protocol, we called ELPIDA. The proposed implementation is intended to reduce power consumption of end devices in WSNs application, even if this means to increase the consumption of non energy critical nodes. In considered simulation scenario (i.e. Fig. 7), we assumed PAN coordinator and routers to be mains-powered. Energy consumption and throughput, intended as the rate of packets correctly received by the root destination node, have been evaluated through simulations comparing data link OPNET models of IEEE (from IPP HURRAY! Research Group), native DSME and ELPIDA. Simulations and MAC protocols comparisons have been performed varying the sending rate of wireless sensors, i.e. the number of data packets generated each second and put in queue to be transmitted in US-RLs. Data frames are sent by wireless sensors only during GTSs (ensuring a fixed latency) and, in order to keep the superframe structure as constant as possible, BI is the same for all MACs. Effect of interferers and loss of synchronism are not considered in following results. Fig. 8 shows a comparison of MAC protocols throughput. For sending rates up to 4 pkts/s, the throughput increases in all three schemes. In IEEE exceeding that threshold leads to throughput saturation due to GTS bandwidth limit. Reaching this limit delay increases exponentially and MAC incoming frame queue begins to grow until packets are discarded. On the other side, both IEEE e DSME based models are allowed to increase their throughput linearly with sending rate. This is due to multi-sf structure and to frequency multiplexing: available GTSs are multiplied in DSME and throughput reaches 2.5 times the one of IEEE for sending rate of 10 pkts/s. These results clearly show that DSME is the right choice 8

11 Figure 8: Simulated throughput vs. sending rate. in applications requiring significant network load. Fig. 9 shows end devices energy consumption, obtained by averaging the contribution of all 12 nodes in a 20 minutes long time window. As expected, the IEEE energy demand Figure 9: Simulation results showing energy consumed by end devices. increases slowly up to a sending rate of 4 pkts/s. Once GTS link bandwidth saturates, also the energy consumption settles since no more packets can be delivered. On the other hand, since both native DSME and ELPIDA energy consumption is proportional to the sending rate, the difference between energy values is constant despite the sending rate. In these MAC models GTS link bandwidth saturates with a sending rate of 18 pkts/s. It can be easily realized that DSME power consumption, despite the significant increase in throughput, is always lower than IEEE ELPIDA approach, as forecasted in Sec. 4, drastically decreases power demand up to a factor 9 if compared with IEEE and up to 7 with respect to DSME. Hence, ELPIDA represents a viable solution in destination-oriented, 9

12 ultra low-power, WSNs in which nodes are battery or energy harvesting powered. The incremented throughput, however, is expected to impact on PAN coordinator and router devices energy consumption performance. Routing devices and traffic sink, in order to meet increasing throughput requests, allocate longer US-RLs to their child devices. This increases the time they spend in RX mode, proportionally to the workload. Again, higher wireless sensor bandwidth reflects in an increased need for bandwidth in routing devices US-RLs, prolonging the time they spend in transmission (TX) mode. To achieve a deeper insight on how this behavior impacts on overall network power consumption, simulations have been carried out collecting results for specific classes of devices. Fig. 10 shows a comparison of simulation results for energy consumed by routers, averaged over all 3 available routers in a period of 20 minutes. In DSME energy consumption depends on the number of DSME-GTSs in a US-RL and presents a visible step each time a new DSME- GTS is reserved. On the other hand, since in IEEE based network there is no increase in links throughput, routers consumption depends only on the number of children. Figure 10: Simulation results showing energy consumed by routers. 6 Conclusion This paper presents a new MAC protocol, ELPIDA, for low-power WSNs with special attention to cluster-tree topology. The aim of this work is the reduction of power consumption for energy critical nodes (end devices) optimizing the transceiver usage at data-link layer. Proposed implementation is based on IEEE e DSME standard and, minimizing the time end devices spend in frame reception, is particularly suitable for destination-oriented traffic. For comparison purposes, different protocols have been analyzed and simulated both from a power consumption and throughput points of view. Simulations show outstanding performance compared to IEEE and native IEEE e DSME, confirming analysis results. The proposed MAC implementation rationalizes overall network power consumption shifting it toward non energy critical nodes (router devices and PAN coordinator). Thus, ELPIDA represents a viable solution in destination-oriented, ultra low-power, WSNs in which end nodes are battery or energy harvesting powered. Future works include ELPIDA implementation on our test bed nodes to show its experi- 10

13 mental effectiveness and robustness on larger networks, in presence of interferers and channel effects. Acknowledgment This work was supported by RENDEZ VOUS project, P.O. Puglia FESR-Asse I, Linea 1.2, Azione

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