Quick Look at Sensor Networks

1. Quick Look at Sensor Networks Elke A. Rundensteiner Based on material collated by Silvia Nittel, and others. CS525

2. Overview – Sensor Networks • Motivation & Applications • Platform & Power • Networking Underpinning

3. Motivation • Trends: • Developments of new sensor materials • Miniaturization of microelectronics • Wireless communication • Consequences: • Embedding devices into almost any man-made and some natural devices, and • connecting the device to an infinite network of other devices, to perform tasks, without human intervention. • Information technology becomes omnipresent. • ”Pervasive Computing”:The idea that technology is to move beyond the personal computer to everyday devices with embedded technology and connectivity as computing devices become progressively smaller and more powerful.

4. Embedded Networked Sensing Potential • Micro-sensors, on-board processing, and wireless interfaces all feasible at very small scale • can monitor phenomena “up close” in non-intrusive way • Will enable spatially and temporally dense environmental monitoring • Embedded & Networked Sensing will reveal previously unobservable phenomena Habitat Monitoring Storm petrels on Maine’s Great Duck Island Contaminant Transport Marine Microorganisms Vehicle Detection

5. Multiscale Observation and Fusion: Example, Regional (or greater) scale to local scale • Satellite, airborne remote sensing data sets at regular time intervals • coupled to regional-scale “backbone” sensor network for ground-based observations • fusion, interpolation tools based on large-scale computational models Small-scale Sensor network images from Susan Ustin, UC Davis

6. Overview • Motivation & Applications • Platforms and Power • Networking

7. Sensor Network • “Sensor Node”: • Tiny vanilla computer with operating system, on-board sensor(s) and wireless communication (“PC on a pin tip”) • Trend towards low-cost, micro-sized sensors • Use of wireless low range RF communication • Batteries as energy resource • “Sensor Network” • Massive numbers of “sensors” in the environment that measure and monitor physical phenomena • Local interaction and collaboration of sensors • Global monitoring • Tightly coupled to the physical world to sense and influence it

8. Mica2 and Mica2Dot 1 inch • Processor: • ATmega128 CPU • RAM/Storage: • Chipcon CC1000 • Manchester encoding • Tunable frequency • Byte spooling • Power usage scales with range

9. Light (Photo) Temperature Acceleration 2 axis Resolution: ±2mg Magnetometer Resolution: 134mG Microphone Tone Detector Sounder 4.5kHz Mica Sensor Board

10. A Network S. Madden, UBerkeley

11. Wireless Sensor Networks • They present a range of computer systems challenges because they are • closely coupled to the physical world with • all its unpredictable variation, noise, and asynchrony; • they involve many energy-constrained, resource-limited devices operating in concert; • they must be largely self-organizing and self-maintaining; and • they must be robust despite significant noise, loss, and failure.

12. Architecture Application layer Application: Events, Reactions Data model, Declarative queries (temp-spatial) DB layer Data aggregation, Query processing Adaptive topology, Geo-Routing Network layer MAC, time, location Physical layer Phy: comm, sensing, actuation Source: Deborah Estrin, UCLA

13. Overview • Motivation & Applications • Platforms & Power • Networking

14. Communication using Radio Listening & receiving signals Broadcasting radio signals

15. PicoRadio and Radio propagation • Energy required to transmit signals in distance d • Communication is huge battery drain • Indoor has lots of other complications • Small energy consumption => short range communication • Multi-hop routing required to achieve distance • Routes around obstacles • Requires discovery, network topology formation, maintenance • may dominate cost of communication • Energy to receive • Dominated by listening time (potential receive) • Device has a total “lifespan” • Radio must be OFF most of the time!

16. Low-level Networking • Physical Layer • Low-range radio broadcast/receive • Wireless (wiSeNets) • MAC: Media Access Control • Controls when and how each node can transmit in the wireless channel (“Admission control”) • Objectives: • Channel utilization • How well is the channel used? (bandwidth utilization) • Latency • Delay from sender to receiver; single hop or multi-hop • Throughput • Amount of data transferred from sender to receiver per time unit • Fairness • Can nodes share the channel equally?

17. Dominant factor MAC Design Decisions • Energy is primary concern in sensor networks • What causes energy waste? • Collisions • Control packet overhead • Overhearing unnecessary traffic • Long idle time • bursty traffic in sensor-net apps • Idle listening consumes 50—100% of the power for receiving (Stemm97, Kasten)

18. Networking • Network Architecture: Can we adapt Internet protocols and “end to end” architecture to SN? • Internet routes data using IP Addresses in Packets and Lookup tables in routers • Many levels of indirection between data name and IP address, but basically address-oriented routing • Works well for the Internet, and for support of Person-to-Person communication • Embedded, energy-constrained, unattended system • cannot tolerate communication overhead of indirection • sensor network architecture needs • Minimal overhead, and Data centric routing

19. Data-centric Routing • Named-data as a way of tasking motes, expressing data transport request (data-centric routing) • Basically: • “send the request to sensors that can deliver the data, I do not care about their address” • Initial approaches in literature: • Some form of tree-based routing • Query sent out from server to motes • Sink-Tree built to carry data from motes to server

20. A B C D F E Communication In Sensor Nets • Radio communication has high link-level losses • typically about 20% @ 5m • Ad-hoc neighbor discovery • Tree-based routing

21. Query A B C D F E Tree Routing Parent Node Children Nodes

22. Tree building • Queries/Request • What goes in query? • Where does query go? • Neighbor selection • How does mote select upstream neighbor for data? • Asymmetric links • Unidirectional links

23. Tree building • Dynamics • How often do you send out a new query? • How often do you select a new upstream path ? • Design tree building protocol • From query source to data producer(s) and back • Multihop ad-hoc routing •  reliable routing is essential!

24. Basic Primitives • Single Hop packet loss characteristics -> link quality • Environment, distance, transmit power, temporal correlation, data rate, packet siz • Services for High Level Protocols/Applications • Link estimation • Neighborhood management • Reliable multi-hop routing for data collection

25. Neighborhood Management • Maintain link estimation statistics and routing information of each neighboring sensor node • Issue: • Density of nodes can be high but memory of nodes is limited • At high density, many links are poor or asymmetric • Neighborhood Management • Question: when table becomes full, • should we add new neighbor? • If so, evict old neighbor? • Similar to • frequency estimation of data streams, or • classical cache policy

26. Reliable Routing • 3 core components for Routing • Neighbor table management • Link estimation • Routing protocol

27. Quick Summary • Motivation & Applications • Platforms & Power • Networking