1. Lecture 8: Wireless Sensor Networks

2. Announcement  Midterm EXAM : 5:00 – 6:15 pm March 28 (Thursday)  Midterm project report due 4/4 (Email submission)  No class on 4/4 due to Chancellor's Inauguration  “we ask that all classes be cancelled beginning at 12:30 for the remainder of the day. Classes will resume on Friday morning, April 5, 2013” – Provost  Project Presentation on April 9

3. Sensor Node Hardware  Two main components  Sensor Board  Base (Processor + Transceiver)  Base + Sensor Board(s) = Sensor Node

4. Sensor Board  Light  Ultraviolet  IR  Visible Light  Color sensors  Magnetic  Sound  Ultrasound  Accelerometer  Temperature  Pressure  Humidity  Touch sensors 2.25 in Microphone Accelerometer Lig ht Temperature Sounder Magnetometer 1.25 in

5. Sensor Node Hardware Power Unit ANTENNA Sensor ADC ProcessorMemory Transceiver SENSING UNIT PROCESSING UNIT

6. Properties of wireless sensor networks  Sensor nodes (SN) monitor and control the environment  Nodes process data and forward data via radio  Integration into the environment, typically attached to other networks over a gateway (GW)  Network is self-organizing and energy efficient  Potentially high number of nodes at very low cost per node SN GW SN GW Bluetooth, TETRA, … Ethernet SN GPRS WLAN ALARM!

7. Wireless Sensor Networks (WSN) Commonalities with MANETs – Self-organization, multi-hop – Typically wireless, should be energy efficient Differences to MANETs – Applications: MANET more powerful, more general  WSN more specific – Devices: MANET more powerful, higher data rates, more resources  WSN rather limited, embedded, interacting with environment – Scale: MANET rather small (some dozen devices)  WSN can be large (thousands) – Basic paradigms: MANET individual node important, ID centric  WSN network important, individual node may be dispensable, data centric

8. Sensor Motes Timeline Mica “Open Experimental Platform” WeC “Smart Rock” Rene’ “Experimentation” Dot “Scale” Spec “Mote on a chip” Telos “Integrated Platform” Mica2Dot Mica2 2006 20052004200320022001200019991998 IMote MicaZ Stargate 2.0 & IMote 2 Stargate 2007 SunSpot

9. Promising applications for WSNs  Machine and vehicle monitoring  Sensor nodes in moveable parts  Monitoring of hub temperatures, fluid levels …  Health & medicine  Long-term monitoring of patients with minimal restrictions  Intensive care with relative great freedom of movement  Intelligent buildings, building monitoring  Intrusion detection, mechanical stress detection  Environmental monitoring, person tracking  Monitoring of wildlife and national parks  Cheap and (almost) invisible person monitoring  Monitoring waste dumps, demilitarized zones  … and many more: logistics (total asset management, RFID), telematics …

10. CodeBlue: WSNs for Medical Care  NSF, NIH, U.S. Army, Sun Microsystems and Microsoft Corporation  Motivation - Vital sign data poorly integrated with pre-hospital and hospital-based patient care records Reference: http://www.eecs.harvard.edu/~mdw/proj/codeblue/

11. Wearable Patient Monitoring Application (ECG) Through Wireless Networks  Wearable Resilient Electrocardiogram (ECG) networked sensor device used for patient monitoring Wireless ECG medical sensor Software GUI interface

12. Sensor Networks: Research Areas Real-World Integration – Gaming, Tourism – Emergency, Rescue – Monitoring, Surveillance Self-configuring networks – Robust routing – Low-power data aggregation – Simple indoor localization Managing wireless sensor networks – Tools for access and programming – Update distribution Long-lived, autonomous networks – Use environmental energy sources

13. Routing in WSNs is different  No IP addressing, but simple, locally valid IDs  Example: directed diffusion  Interest Messages  Interest in sensor data: Attribute/Value pair  Gradient: remember direction of interested node  Data Messages  Send back data using gradients  Hop count guarantees shortest path Sink

14. TTDD: A Two-tier Data Dissemination Model for Large-scale Wireless Sensor Networks

15. A Sensor Network Example

16. Assumptions  Fixed source and sensor nodes, mobile or stationary sinks  Nodes densely applied in large field  Position-aware nodes, sinks not necessarily  Once a stimulus appears, sensors surrounding it collectively process signal, one becomes the source to generate the data report

17. Sensor Network Model Source Stimulus Sink

18. Mobile Sink Excessive Power Consumption Increased Wireless Transmission Collisions State Maintenance Overhead

19. Goal, Idea  Efficient and scalable data dissemination from multiple sources to multiple, mobile sinks  Two-tier forwarding model  Source proactively builds a grid structure  Localize impact of sink mobility on data forwarding  A small set of sensor node maintains forwarding state

20. Grid setup  Source proactively divide the plane into α X α square cells, with itself at one of the crossing point of the grid.  The source calculates the locations of its four neighboring dissemination points  The source sends a data-announcement message to reach these neighbors using greedy geographical forwarding  The node serving the point called dissemination node  This continues…

21. TTDD Basics Source Dissemination Node Sink Data Announcement Query Data Immediate Dissemination Node

22. TTDD Mobile Sinks Source Dissemination Node Sink Data Announcement Data Immediate Dissemination Node Immediate Dissemination Node Trajectory Forwarding Trajectory Forwarding

23. TTDD Multiple Mobile Sinks Source Dissemination Node Data Announcement Data Immediate Dissemination Node Trajectory Forwarding Source

24. Trajectory Forwarding

25. Conclusion  TTDD: two-tier data dissemination Model  Exploit sensor nodes being stationary and location-aware  Construct & maintain a grid structure with low overhead  Proactive sources  Localize sink mobility impact  Infrastructure-approach in stationary sensor networks  Efficiency & effectiveness in supporting mobile sinks

26. The Future of WSNs  Fundamental requirements today only partially fulfilled  Long life-time with/without batteries  Self-configuring, self-healing networks  Robust routing, robust data transmission  Management and integration  Think of new applications  Intelligent environments for gaming  …  Still a lot to do…  Integration of new/future radio technologies  Cheap indoor localization (+/- 10cm)  More system aspects (security, middleware, …)  Prove scalability, robustness  Make it cheaper, simpler to use  Already today: Flexible add-on for existing environmental monitoring networks

27. Major References  TTDD: http://portal.acm.org/citation.cfm?id=1160112http://portal.acm.org/citation.cfm?id=1160112  “ A survey on sensor networks” http://www- net.cs.umass.edu/cs791_sensornets/papers/akyildiz2.p df  Routing techniques in wireless sensor networks: A Survey http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumb er=1368893&userType=inst