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

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

3. 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. 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. 5 Multiscale Observation and Fusion: Example, Regional (or greater) scale to local scale images from Susan Ustin, UC Davis 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

6. 6 Overview Motivation & Applications Platforms and Power Networking

7. 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. 8 UC Berkeley Family of Motes

9. 9 Mica2 and Mica2Dot Processor: ATmega128 CPU RAM/Storage: Chipcon CC1000 Manchester encoding Tunable frequency Byte spooling Power usage scales with range 1 inch

10. 10 Mica Sensor Board Light (Photo) Temperature Acceleration 2 axis Resolution: ±2mg Magnetometer Resolution: 134  G Microphone Tone Detector Sounder 4.5kHz

11. 11 A Network S. Madden, UBerkeley

12. 12 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.

13. 13 Architecture Data aggregation, Query processing Adaptive topology, Geo-Routing MAC, time, location Phy: comm, sensing, actuation Data model, Declarative queries Application: Events, Reactions Network layer (temp-spatial) DB layer Physical layer Application layer Source: Deborah Estrin, UCLA

14. 14 Overview Motivation & Applications Platforms & Power Networking

15. 15 Communication using Radio Broadcasting radio signals Listening & receiving signals

16. 16 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! PicoRadio and Radio propagation

17. 17 ISO/OSI Protocol Stack Physical Data Link Network Transport Session Presentation Application 7 Layer ISO/OSI Reference Model The Network Card The Internet Protocols Internet Application The End Computer System View Transport Control Protocol (TCP) Internet Protocol (IP) *) International Standard Organization's Open System Interconnect

18. 18 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?

19. 19 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) Dominant factor

20. 20 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

21. 21 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

22. 22 Communication In Sensor Nets Radio communication has high link-level losses typically about 20% @ 5m Ad-hoc neighbor discovery Tree-based routing A B C D F E

23. 23 Tree Routing A B C D F E Query Parent Node Children Nodes

24. 24 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

25. 25 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!

26. 26 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

27. 27 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

28. 28 Reliable Routing 3 core components for Routing Neighbor table management Link estimation Routing protocol

29. 29 Quick Summary Motivation & Applications Platforms & Power Networking