Transcript Lecture 8
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 “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 Sensor Node Hardware Two main components Sensor Board Base (Processor + Transceiver) Base + Sensor Board(s) = Sensor Node Sensor Board Light Ultraviolet IR Visible Light Color sensors Magnetic Sound Ultrasound Accelerometer Temperature Pressure Humidity Touch sensors Sounder Lig Temperature ht Accelerometer 1.25 in Magnetometer 2.25 in Microphone Sensor Node Hardware SENSING UNIT PROCESSING UNIT Processor Transceiver Sensor ADC Memory Power Unit ANTENNA 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 GW SN SN Bluetooth, TETRA, … SN SN SN SN GW SN SN SN SN GW GW SN SN 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 Sensor Motes Timeline Rene’ Mica “Experimentation” “Open Experimental Platform” Telos IMote “Integrated Platform” WeC Stargate 2.0 & IMote2 “Smart Rock” MicaZ Mica2Dot 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Dot “Scale” Spec “Mote on a chip” Mica2 Stargate SunSpot Promising applications for WSNs Machine and vehicle monitoring Health & medicine Intrusion detection, mechanical stress detection Environmental monitoring, person tracking Long-term monitoring of patients with minimal restrictions Intensive care with relative great freedom of movement Intelligent buildings, building monitoring Sensor nodes in moveable parts Monitoring of hub temperatures, fluid levels … 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 … 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/ 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 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 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 TTDD: A Two-tier Data Dissemination Model for Large-scale Wireless Sensor Networks A Sensor Network Example 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 Sensor Network Model Sink Stimulus Source Sink Mobile Sink Excessive Power Consumption Increased Wireless Transmission Collisions State Maintenance Overhead 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 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… TTDD Basics Dissemination Node Data Announcement Source Data Sink Query Immediate Dissemination Node TTDD Mobile Sinks Dissemination Node Trajectory Forwarding Data Announcement Source Immediate Dissemination Node Data Sink Immediate Dissemination Node Trajectory Forwarding TTDD Multiple Mobile Sinks Dissemination Node Trajectory Forwarding Data Announcement Source Immediate Dissemination Node Data Source Trajectory Forwarding Conclusion TTDD: two-tier data dissemination Model Proactive sources Exploit sensor nodes being stationary and location-aware Construct & maintain a grid structure with low overhead Localize sink mobility impact Infrastructure-approach in stationary sensor networks Efficiency & effectiveness in supporting mobile sinks The Future of WSNs Fundamental requirements today only partially fulfilled Think of new applications Intelligent environments for gaming … <your idea here> Still a lot to do… Long life-time with/without batteries Self-configuring, self-healing networks Robust routing, robust data transmission Management and integration 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 Major References TTDD: http://portal.acm.org/citation.cfm?id=1160112 “ A survey on sensor networks” http://wwwnet.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