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Lecture 8: Wireless Sensor Networks

Lecture 8: Wireless Sensor Networks. 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

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Lecture 8: Wireless Sensor Networks

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  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 Sounder Temperature Light Accelerometer 1.25 in Magnetometer 2.25 in Microphone

  5. Transceiver Sensor ADC Processor Memory ANTENNA Power Unit Sensor Node Hardware 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 ALARM! ALARM! ALARM! GW Bluetooth, TETRA, … SN SN SN SN SN SN GW SN SN SN SN GW SN GW 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, moregeneral  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” Rene’ “Experimentation” Telos “Integrated Platform” IMote Stargate 2.0 & IMote2 WeC “Smart Rock” MicaZ Mica2Dot 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Spec“Mote on a chip” Dot “Scale” Mica2 Stargate 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 Software GUI interface Wireless ECG medical sensor

  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. Sink Sink Sensor Network Model Stimulus Source

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

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

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

  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 onlypartially 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 … <your idea here> 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 existingenvironmental monitoring networks

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

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