An Overview on State of The Art and Real-World Deployments of Wireless Sensor Networks

Transcription

1 An Overview on State of The Art and Real-World Deployments of Wireless Sensor Networks Luca Mottola ( Networked Embedded Systems Group SICS Guest Lecture Distributed Information System Course, Uppsala (Sweden), November 22nd 2010 A part of Swedish ICT

2 Who Am I? after some hours of debugging Ph.D. in Computer Engineering Politecnico di Milano (Italy), 2008 thesis: Programming Wireless Sensor Networks: From Physical to Logical Neighborhoods, supervised by Prof. Gian Pietro Picco In 2007, research scholar at the University of Southern California (USA) Landed in Sweden at the beginning of 2009 Now a Senior Researcher at Swedish Institute of Computer Science More info at

3 Computing on the Internet Interaction between people and human-mediated data sources #nodes #users Nodes are resource-rich Communication among geographically distributed nodes Focus: human-centered interactive decision making

4 Cooperating Objects Interaction between people and the instrumented world (e.g., sensors, actuators) #nodes >> #users Answers are obtained by fusing real-time information from distributed nodes Nodes are resource-scarce Focus: support human-supervised autonomous decision making

5 Wireless Sensor Networks Enabled by miniaturization of processing, communication, sensing and actuating devices Distinctive feature: self-organizing topology with multi-hop communication many cheap devices with short-range communication more coverage with less energy (and no wires!)

6 Applications Examples: Wildlife monitoring Glacier monitoring Cattle herding Ocean monitoring Vineyard monitoring Cold chain monitoring Rescue of avalanche victims Vital sign monitoring Tracking vehicles Sniper localization Volcano monitoring Tunnel monitoring and rescue

7 Example: Volcano Monitoring (adapted from M. Welsh)

8 Anatomy of a WSN Node

9 Anatomy of a WSN Node

10 Example: TelosB/TMote Sky TI MSP 430 (16 bit RISC) 8 MHz 10 KB RAM 48 KB code, 1MB flash Chipcon CC2420 radio IEEE compliant 50 m. range indoor, 250 m. range outdoor bandwidth 250 kbits/s On-board antenna Temperature, light, and humidity sensors built-in

11 Hello World Demo Humidity Sensing A tiny sensing application one node senses humidity at every second the other node turns red if humidity is above 50%, or green otherwise

12 Hello World Demo Steal the Light! (adapted from M. Lunden)

13 WSN Challenges: Power Power consumption devices are battery-powered, meant to operate unmanned for a long period of time communication is typically the biggest energy drain duty cycle is critical: nodes sleep for most of the time communication ~ma, stand-by ~μa TMote mote always on: ~8 days; 2% duty cycle (1.2s/min): 9 months

14 Speaking of Radio.. No radio duty-cycle Radio duty-cycle

15 WSN Challenges: Reliability Reliability wireless link quality fluctuates based on environment topology changes as the WSN operates! nodes are often deployed in a hostile environment and may fail the application/network must self-organize!

16 The Woes of Wireless Non-isotropic range, asymmetric links Collisions, hidden terminal problem What-you-see-is-not-what-you-get topologies e.g., good connection to far nodes and bad to close ones

17 A Reference Architecture

18 Operating Systems OSs for WSNs different from mainstream ones - basic run-time support for application programs - no support for user interaction Programs are cross-compiled and linked with the OS library: the resulting binary is deployed on the WSN node Most popular: TinyOS - common alternatives: Contiki, Mantis Main differences: model of concurrency, support for dynamic linking

19 Medium Access Control (MAC) Only goals: avoid packet collisions and turn off the radio whenever possible Much simpler than conventional MACs some features are demanded to application code CSMA (Carrier Sense) with preamble sampling and TDMA (Time Division) are dominant CSMA good for changing topologies, may suffer under heavy load TDMA guarantees predictable performance, needs time synch CSMA TDMA

20 Routing sink Concern: energy consumption WSN routing is different: conventional protocols based on addresses identifying the target (e.g., unicast or multicast IP addresses) WSN nodes are rarely relevant per se: it is their (individual or collective) features that matter many-to-one, one-to-many and many-to-many vs. one-to-one Typically, attribute-based routing is used source message forwarding based on the nature of data similar to content-based routing source

21 Time Synchronization Often necessary to correlate the data to the time it was sampled e.g., structural monitoring, earthquake detection Nodes have different times differences in clock quartzes and in their drifts well-known problem in distributed systems (NTP): peculiarity here is wireless and energy-awareness Several protocols available precision down to milliseconds require periodic network-wide message exchanges

22 Node Localization It is often necessary to know the physical location of a node interpret sensed data, determine span of actuation often determined at deployment time and known to both nodes and gateway What if location is not known? assume nodes are GPS-equipped easy and precise but energy hungry use radio-based localization e.g., based on RSSI

23 In Practice, However Each component is often built separately The programmer is forced to deal with low-level details instead of the application logic

24 WSN Challenges: Programming Ease of programming currently recognized as a major hampering factor and technology enabler WSN programming mostly done in ad-hoc fashion close to the OS - largest coding effort in low-level details - difficult to port and re-use - performance issues due to bugs Great Duck Island: average yield 58% [SenSys 04] Redwood Trees: average yield 40% [SenSys 05] Volcano: average yield 69% [OSDI 06]

25 WSN Programming Wide variety of application requirements Inherent tension between: the desire to shield programmers from complexity the need to enable cross-layer design Habitat monitoring decentralized Wildlife monitoring Wireless Sensor and Actor Networks Smart ambient January 28th, 2008 centralized homogeneous heterogeneous Healthcare

26 Two Extremes Common classification: node-centric code describes behavior of individual nodes e.g., nesc macro-programming code describes behavior of the system as a whole

27 The Torre Aquila Deployment (Trento, Italy) M. Ceriotti, L. Mottola, G. P. Picco, A. L. Murphy, S. Guna, M. Corrà, M. Pozzi, D. Zonta, and P. Zanon. "Monitoring Heritage Buildings with Wireless Sensor Networks: The Torre Aquila Deployment. In IPSN/SPOTS, Best paper award.

28 Motivation Heritage buildings require maintenance and careful assessment Typically achieved with wired data loggers cumbersome and invasive especially in the presence of works of art WSNs as a viable alternative untethered monitoring minimum invasiveness high sensing granularity flexibility and ease of relocation Traditional data logger WSN node

29 Torre Aquila 31-meter tall medieval tower part of the complex of Castello del Buonconsiglio in Trento, Italy The 2 nd floor contains the Ciclo dei 12 mesi internationally-renowned frescoes, attracting thousands of visitors each year Originally the Eastern gate to the city today, surrounded by high volume of vehicular traffic Concerns due to the plan of diverting traffic into a road tunnel near the tower

30 Deployment in Torre Aquila Environmental Acceleration Deformation THIRD FLOOR FOS FOS SECOND FLOOR joint FIRST FLOOR NORTH SECTION

31 Hardware Base Node, Environmental/Deformation Sensors WSN node: TRETEC 3MATE! 3MATE! environmental board analog temperature (±.5 C) relative humidity (± 3%) light (10lx to 1000lx) Deformation measured with fiber optic sensors read-out unit, laser pulser, optical receiver interfaced to 3MATE! via serial protocol

32 Hardware Acceleration Nodes Tri-axial analog MEMS inertial sensor ± 2g, 1.5 KHz bandwidth, ±1mg over 100 Hz bandwidth calibration with shake table and piezoeletric sensors FRAM chip faster read/write enables accel sensing up to 1KHz rate energy efficient much higher number of R/W operations

33 Software Functionality fully decoupled Asynchronous interactions through the TeenyLIME middleware Sampling and Tasking to drive sensing based on user parameters Data Collection to report sensed data reliably Data Dissemination to distribute user parameters Time Synchronization to correlate readings

34 Software Sampling & Data Collection Different classes of traffic Bursty, high-rate w/ strong reliability (compressed) vibration data Node type Environmental Deformation Acceleration Low-rate w/ weak reliability environmental, deformation data Best effort system monitoring Operating parameters Sampling period P # of sampling sessions N # of samples averaged A Sampling period P # of sampling sessions N Sampling frequency F Sampling duration D # of sampling sessions N Typical values 10 min infinite min infinite 200 Hz 20 s infinite

35 Sampling & Data Collection Routing Details Hop-by-hop reliability scheme entirely implemented using TeenyLIME s functionality Child Parent cache cache cache cache send(tuple 6) send(tuple 7) send(tuple 8) send(tuple 9) retrieve(tuple 7)

36 (Preliminary) Data Analysis Deformation The breath of the structure Vibrational Modes Vibration Monitoring D. Zonta Heritage et al. Buildings Real-Time with WSNs: Health The Monitoring Torre Aquila of Deployment of Historic Buildings with Wireless Sensor Networks 2009 Matteo Ceriotti and In Proc. Luca Mottola of the 7th Int. Conf. On Structural Health Monitoring, 2009.

37 System Performance Lifetime is over one year acceleration nodes are the main drain The routing protocols guarantee very high reliability even for high-rate acceleration data Cumulative loss rate (log scale) Data loss 1e-05 Class I Traffic Class II Traffic 1e-06 30/08 01/09 03/09 05/09 07/09 09/09 11/09 13/09 15/09 Date

38 Lessons Learned Thick walls drastically affect wireless propagation small changes in node placement modify the topology Percentage of time motes are tempting 1 0 #152 #151 #148 #146 #143 # Sept - 09 Sept #152 #151 #148 #146 #143 # Sept - 14 Sept 1 Hop 2 Hops 3 Hops 4 Hops 5 Hops 6 Hops Moved the sink node by 1 meter!

39 Questions?