1. INT598 Sensor Networks Silvia Nittel Spatial Information Science & Engineering University of Maine Fall 2006

2. INT598: IGERT in Sensor Science, Engineering and Informatics 2 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 IGERT

3. INT598: IGERT in Sensor Science, Engineering and Informatics 3 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Overview Motivation & Applications Platforms, Operating Systems, Power Networking Protocols, naming, routing Data Collection and Aggregation

4. INT598: IGERT in Sensor Science, Engineering and Informatics 4 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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.

5. INT598: IGERT in Sensor Science, Engineering and Informatics 5 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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

6. INT598: IGERT in Sensor Science, Engineering and Informatics 6 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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

7. INT598: IGERT in Sensor Science, Engineering and Informatics 7 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Overview Motivation & Applications Platforms, Operating Systems, Power Networking Protocols, naming, routing Data Collection and Aggregation In-network data aggregation

8. INT598: IGERT in Sensor Science, Engineering and Informatics 8 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Emergence of WiSeNets 1994 Pottie and Kaiser propose Low Power Wireless Integrated Microsensors DARPA Sensit Program (Sensor Information Technology) Late 97-98 handhelds emerge Palm platform ITSY, BWRC PicoRadio, etc. Matchbox PCs Bluetooth promised Berkeley SmartDust 1999 WeC mote offshoot 2000 Mote/TinyOS platforms WINS finally appears in Linux for Darpa’s Sensit 2002 Mica NEST OEP creates de facto platform 2003 Bluetooth revival 2004 Telos, lowest power mote, supports IEEE 802.15.4

9. INT598: IGERT in Sensor Science, Engineering and Informatics 9 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Abbreviations Sensit Darpa’s Program “Sensor Information Technology” WINS Wireless Integrated Network Sensor Platforms Developed by Sensoria Corporation for Darpa’s Sensit program NEST Network Embedded Systems OEP Open Experimental Platform (a middleware for sensor networks)

10. INT598: IGERT in Sensor Science, Engineering and Informatics 10 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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

11. INT598: IGERT in Sensor Science, Engineering and Informatics 11 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 UC Berkeley Family of Motes

12. INT598: IGERT in Sensor Science, Engineering and Informatics 12 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Mica2 and Mica2Dot Processor: ATmega128 CPU RAM/Storage: Chipcon CC1000 Manchester encoding Tunable frequency Byte spooling Power usage scales with range 1 inch

13. INT598: IGERT in Sensor Science, Engineering and Informatics 13 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Basic Sensor Board Light (Photo) Temperature Prototyping space for new hardware designs

14. INT598: IGERT in Sensor Science, Engineering and Informatics 14 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Mica Sensor Board Light (Photo) Temperature Acceleration 2 axis Resolution: ±2mg Magnetometer Resolution: 134  G Microphone Tone Detector Sounder 4.5kHz

15. INT598: IGERT in Sensor Science, Engineering and Informatics 15 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Mica Weather Board Total Solar Radiation Photosynthetically Active Radiation Resolution: 0.3A/W Relative Humidity Accuracy: ±2% Barometric Pressure Accuracy: ±1.5mbar Temperature Accuracy: ±0.01 o C Acceleration 2 axis Resolution: ±2mg Designed by UCB w/ Crossbow and UCLA Revision 1.5 Revision 1.0

16. INT598: IGERT in Sensor Science, Engineering and Informatics 16 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Telos: New OEP Mote Single board philosophy Robustness, Ease of use, Lower Cost Integrated Humidity & Temperature sensor First platform to use 802.15.4 CC2420 radio, 2.4 GHz, 250 kbps (12x mica2) 3x RX power consumption of CC1000, 1/3 turn on time Same TX power as CC1000 Motorola HCS08 processor Lower power consumption, 1.8V operation, faster wakeup time 40 MHz CPU clock, 4K RAM Package Integrated onboard antenna +3dBi gain Removed 51-pin connector Everything USB & Ethernet based 2/3 A or 2 AA batteries Weatherproof packaging Support in upcoming TinyOS 1.1.3 Release Co-designed by UC Berkeley and Intel Research Available from Moteiv (moteiv.com)

17. INT598: IGERT in Sensor Science, Engineering and Informatics 17 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 COTS-BOTS (UCB) Commercial Off-The-Shelf roBOTS 5” x 2.5” x 3” size <$250 total 2-axis accelerometer

18. INT598: IGERT in Sensor Science, Engineering and Informatics 18 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Robomote (USC) Less than 0.000047m 3 $150 each Platform to test algorithms for adaptive wireless networks with autonomous robots

19. INT598: IGERT in Sensor Science, Engineering and Informatics 19 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 A Network S. Madden, UBerkeley

20. INT598: IGERT in Sensor Science, Engineering and Informatics 20 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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.

21. INT598: IGERT in Sensor Science, Engineering and Informatics 21 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Sensor Network Objectives Several classes of systems: Mote herds Collaborative processing arrays (32 bit, 802.11, linux) Networked Info-Mechanical Systems: Autonomy Achieve longevity/autonomy, scalability, performance with: heterogeneous systems in-network processing, triggering, actuation Algorithm/Software challenges Characterizing sensing uncertainty Error resiliency, integrity Statistical and information- theoretic foundations for adaptive sampling, fusion Programming abstractions, Common services, tools Data modeling, informatics lifetime/autonomy scale Collaborative processing arrays (imaging, acoustics) sampling rate Mote Clusters

22. INT598: IGERT in Sensor Science, Engineering and Informatics 22 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Sensor Network Design Topics Long-lived systems that can be untethered (wireless) and unattended Communication will be the persistent primary consumer of scarce energy resources (MICA Mote: 720nJ/bit xmit, 4nJ/op) Autonomy requires robust, adaptive, self-configuring systems Leverage data processing inside the network Exploit computation near data to reduce communication, achieve scalability Collaborative signal processing Achieve desired global behavior with localized algorithms (distributed control) “The network is the sensor” (Manges&Smith, Oakridge Natl Labs, 10/98) Requires robust distributed systems of hundreds of physically-embedded, unattended, and often untethered, devices.

23. INT598: IGERT in Sensor Science, Engineering and Informatics 23 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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

24. INT598: IGERT in Sensor Science, Engineering and Informatics 24 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Overview Motivation & Applications Platforms, Operating Systems, Power Networking Protocols, naming, routing Data Collection and Aggregation

25. INT598: IGERT in Sensor Science, Engineering and Informatics 25 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Communication using Radio Broadcasting radio signals Listening & receiving signals

26. INT598: IGERT in Sensor Science, Engineering and Informatics 26 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Energy required to transmit signals in distance d Communication is huge battery drain Indoor has lots of other complications Small energy consumption => short range comm Multihop routing required to achieve distance Routes around obstacles Requires discovery, network topology formation, maintenance may dominate cost of communication Energy to receive ~ E*t at short range Dominated by listening time (potential receive) Radio must be OFF most of the time! PicoRadio and Radio propagation

27. INT598: IGERT in Sensor Science, Engineering and Informatics 27 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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

28. INT598: IGERT in Sensor Science, Engineering and Informatics 28 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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?

29. INT598: IGERT in Sensor Science, Engineering and Informatics 29 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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

30. INT598: IGERT in Sensor Science, Engineering and Informatics 30 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Networking Network Architecture: Can we adapt the Internet protocols and the “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 (un-tethered, small-form-factor), unattended systems cannot tolerate communication overhead of indirection Our sensor network architecture needs Minimal overhead Data centric routing

31. INT598: IGERT in Sensor Science, Engineering and Informatics 31 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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” Two initial approaches in literature: Derived from multicast-routing perspective where you name a logical group of sensor nodes (Diffusion) Derived from database query language (TinyDB) with stronger semantics on data delivery, timing, sequencing Commonality is tree-based routing Query sent out from microserver to motes Sink-Tree built to carry data from motes to microserver

32. INT598: IGERT in Sensor Science, Engineering and Informatics 32 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Tree Routing A B C D F E Query Parent Node Children Nodes

33. INT598: IGERT in Sensor Science, Engineering and Informatics 33 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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 Route characterization (like ETX) Multiple microservers What about multiple microservers? How does mote select a microserver?

34. INT598: IGERT in Sensor Science, Engineering and Informatics 34 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 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!

35. INT598: IGERT in Sensor Science, Engineering and Informatics 35 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Basic Primitives Single Hop packet loss characteristics Environment, distance, transmit power, temporal correlation, data rate, packet size Services for High Level Protocols/Applications Link estimation Neighborhood management Reliable multihop routing for data collection

36. INT598: IGERT in Sensor Science, Engineering and Informatics 36 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Basic Neighborhood of Devices Services for High Level Protocols/Applications Link estimation Neighborhood management Reliable multihop routing for data collection Direct Reception Large variation in affinity Asymmetric links Long, stable high quality links Short bad ones Link quality varies with traffic load Collisions Distant nodes raise noise floor Many poor “neighbors”

37. INT598: IGERT in Sensor Science, Engineering and Informatics 37 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Neighborhood Management Maintain link estimation statistics and routing information of each neighboring sensor node How large should this table be? O(cell density) * meta-data for each neighbor Issue: Density of nodes can be high but memory of each node 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 which old neighbor? Similar to frequency estimation of data streams, or classical cache policy

38. INT598: IGERT in Sensor Science, Engineering and Informatics 38 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Reliable Routing 3 core components for Routing Neighbor table management Link estimation Routing protocol

39. INT598: IGERT in Sensor Science, Engineering and Informatics 39 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Routing Protocols Ad-hoc routing, Geographic routing Topology Formation Directed Diffusion Rumor/Gossip Routing

40. INT598: IGERT in Sensor Science, Engineering and Informatics 40 © Dr. Silvia Nittel, NCGIA, University of Maine, 2006 Overview Motivation & Applications Platforms, Operating Systems, Power Networking Physical layer, MAC, Protocols Routing Adaptable, Configurable Systems Data Collection and Aggregation