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Wireless Sensor Networks (WSN)

Explore the similarities and differences between WSN and MANET, focusing on their infrastructure, multi-hop communication, resources, and applications, with real examples and details on sensor nodes and network architectures. Learn about deployment challenges, sensing coverage, and localization processes in WSN.

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Wireless Sensor Networks (WSN)

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  1. Wireless Sensor Networks (WSN)

  2. Comparing to MANET • Similarities • No infrastructure • Multi-hop communication • Differences • Nodes are more resource-constrained and more prone to failure • More nodes (up to hundreds or thousands) in a network • Random deployment • Unattended • Longer life time • Trust relationships between sensor nodes (typically belong to the same organization) • Application-specific • …

  3. Usage of Sensor Networks • Environmental observation • Water/air pollution detection • Forest fire detection • Animal habitat monitoring • Military monitoring • Battlefield surveillance • Vehicular traffic monitoring • Tracking the position of the enemy • Building monitoring • Monitoring climate changes/vibration • Healthcare • Being implanted in the human body to monitor medical problems

  4. Some Real Examples • Great Duck Island • A prototype sensor network is deployed to monitor the nesting grounds of elusive seabirds • Biologist get information they need with minimal human disturbance • Vineyard • Embedded sensors are deployed to monitor temperature in a vineyard in Oregon’s Willamette Valley. • Golden Gate Bridge • 200 motes organized in an ad hoc sensor network are used for tracking stress on the bridge • Proactive Health Research Project (Intel) • Help seniors age with dignity and independence, by developing sensor network-based in-home technology prototypes. • Preventive maintenance on an oil tanker in the North Sea (Intel and BP)

  5. Sensor Nodes • MICA2(Motes): a popular research platform at the moment (J. Hill, et al., “The platforms enabling wireless sensor networks,” Comm. of the ACM, June 2004/Vol 47. No. 6, pages 41-46)

  6. Sensor Nodes: MICA2 • The core is a small, low-cost, low-power computer • Atmel Atmega 128L processor (4MHZ), 128 KB on-board flash memory • As powerful as 8088 CPU (in original IBM PC) • Power consumption • 8 milliamps (running), 15 micro-amps (sleep) • One or more sensors can be mounted • Connect to the outside world with radio • Transmission range: 10-200 feet, Rate: 76bps • Power consumption • 25 milliamps (Trans), 10 milliamps (Recv), <1 milliamps (off) • Power supply: 2 AA batteries • 2,000 milliamps-hours (http://computer.howstuffworks.com/mote.htm)

  7. Sensor Nodes • Four classes (J. Hill, et al., “The platforms enabling wireless sensor networks,” Comm. of the ACM, June 2004/Vol 47. No. 6, pages 41-46)

  8. Physical layer and MAC sublayer • Related Standard • IEEE 802.15.4 Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs) • Physical layer • 2.4-2.4835 GHZ (worldwide) • 902-928 MHz (North America) or 868-868.6 MHz (Europe) • MAC Sublayer • Contention Access • CSMA-CA • Contention Free

  9. Other MAC Protocols (not complete)

  10. Deployment • Random deployment • Large number of nodes; target area may be remote and/or hostile  manual deployment is impossible in many cases • Problems caused by random deployment • Localization • Sensor nodes must discover their locations after deployment • Coverage • For sensing quality, a certain level of sensing coverage should be achieved. • Security • It is hard to store various encryption keys on nodes, since the neighborhood cannot be know a priori.

  11. Localization • Basic idea of existing schemes • Initial configuration • A small number of beacon nodes • Know their locations by using GPS or being set manually • A large number of nodes (non-beacon nodes) that do not know their locations • Localization process • Beacon nodes send beacon signals to a set of non-beacon nodes • A non-beacon node obtains • Locations of the beacon nodes • Some features related to the distance to these beacon nodes • Received signal strength indicator, Time to arrival, etc. • The non-beacon node estimate its own location based on the obtained information

  12. Sensing Coverage • Objectives • High sensing coverage (full coverage is ideal) • Energy efficient and low cost • Samples of existing work • Sleep scheduling (Ye et al. 03’, Gui et al. 04’) • Over deploying sensor nodes and make spare nodes sleep • Waking up sleeping nodes following certain sleep planning methods • Employing mobile sensor nodes (Wang et al.03’&05’) • Deploy a large fraction of stationary nodes and a small fraction of mobile nodes • Stationary nodes detect sensing holes and notifies mobile nodes • Mobile nodes move to heal the holes

  13. Network Architectures: Flat Sink (data collector) • A large number of sensor nodes form a peer-to-peer ad hoc network • They forward message for each other

  14. Network Architecture: Hierarchical Sink Cluster head • The network is divided into clusters, each cluster has a head (logically or physically) • Ordinary node  cluster head; cluster heads form a backbone

  15. Network Architecture: Hierarchical (J. Hill, et al., “The platforms enabling wireless sensor networks,” Comm. of the ACM, June 2004/Vol 47. No. 6, pages 41-46)

  16. Communication Patterns • A sensor network is a content-based (or data-centric) network • In WSN, networking take place directly on contents (or data) • In Internet/MANET, networking protocols use identifiers of nodes. • Contents can collected, processed and stored in the network • Desirable interaction paradigm in WSN: Publish/Subscribe • Entities can publish data under certain names • Entities can subscribe to updates of such named data (H. Karl, “Ad hoc and sensor networks Chapter 12: Data-centric and content-based networking”)

  17. Reply Node data Type =four-legged animal Instance = elephant Location = [125, 220] Confidence = 0.85 Time = 02:10:35 Naming • Content based naming • Tasks are named by a list of attribute – value pairs • Task description specifies an interest for data matching the attributes • Animal tracking: Request Interest ( Task ) Description Type = four-legged animal Interval = 20 ms Duration = 1 minute Location = [-100, -100; 200, 400]

  18. Communication Patterns • External storage-based pattern • fixed subscriber • Sink-initiated pattern • subscriber initiated • Source-initiated pattern • publisher initiated • Rendezvous-based pattern • Intermediate entities help to match publishers and subscribers

  19. External Storage-based Pattern source sink

  20. Sink-initiated Pattern: Directed Diffusion • The sink periodically broadcasts interest messages to each of its neighbors • Every node maintains an interest cache • Each item corresponds to a distinct interest • No information about the sink • Interest aggregation : identical type, completely overlap rectangle attributes • Each entry in the cache has several fields • Timestamp: last received matching interest • Several gradients: data rate, duration, direction (Intanagonwiwat et al., “Directed Diffusion for wireless sensor networking,”, IEEE/ACM Transactions on Networking (TON), Feb, 2003)

  21. Directed Diffusion • Set up gradient: Constrained or Directional flooding based on location. Gradient Source Interest Sink (Intanagonwiwat et al., “Directed Diffusion for wireless sensor networking,”, IEEE/ACM Transactions on Networking (TON), Feb, 2003)

  22. Directed Diffusion Gradient Source Data Sink (Intanagonwiwat et al., “Directed Diffusion for wireless sensor networking,”, IEEE/ACM Transactions on Networking (TON), Feb, 2003)

  23. Source Sink Source-initiated Patterns Dissemination Node Data Announcement Data Query Immediate Dissemination Node (Ye et al., “TTDD: A Two-tier Data Dissemination Model for Large-Scale Wireless Sensor Networks,” Mobicom’02)

  24. Rendezvous-based pattern • Data with the same name are stored at the same place (Ratnasamy et al., “Data-centric Storage in Sensor Networks with GHT,” Mobile Networks and Applications, 2004.)

  25. Rendezvous-based pattern • Fault tolerance consideration • If a storing fails, it is replaced by another node closest to itself • To protect the stored data, data can be replicated in multiple nodes (Ratnasamy et al., “Data-centric Storage in Sensor Networks with GHT,” Mobile Networks and Applications, 2004.)

  26. Routing • Address-centric (AC) protocol • Each source independently sends data along the shortest path to sink based on the route that the queries took (“end-to-end routing”) • Data-centric (DC) protocol • The sources send data to the sink, but routing nodes en-route look at the content of the data and perform some form of aggregation/consolidation function on the data originating at multiple sources. (Krishnamachari et al., “Modeling data-centric routing in wireless sensor networks”, 2002.)

  27. Data Aggregation Sensing range of A • Types • Removing redundancy • In-network processing Redundancy After aggregation, the redundancy is removed Sensing range of B

  28. Data Aggregation: in-network processing • Aggregation is implemented by three functions • Merging function f, initializer i and evaluator e. • General form <z> = f (<x>,<y>) • <x> and <y> are multi valued partial state records • <z> is partial state record resulting from application of f to <x> and <y> • E.g. f is the merging function of AVERAGE f(<S1,C1>,<S2,C2>)=<S1+ S2, C1 + C2> i(x) = <x,1> e(<S,C>) = S/C where S and C are Sum and Count. f(<3,1>,<5,1>) = <8,2> f(<8,2>,<7,1>) = <15,3> e(<15,3>) = 15/3 = 5 i(7)=<7,1> <3,1> <5,1> i(5)=<5,1> i(3)=<3,1>

  29. Security Issues • Major challenges • Resource constraints in computation, storage and communication • Public key is too expensive • Private key operations in MICA2: a few milliseconds • RSA-based public key operations: tens of seconds (50-60) • ECC-based public key operations: tens of seconds (~30s) • Security mechanisms must be low-cost • Unattended deployment & lack of temper resistance • Must address node compromise

  30. Security Issues • Existing research • Low-cost key management • Pair-wise key & group-wise key • Message and entity Authentication • Securing protocols in sensor networks • Localization • Data aggregation • … • Privacy/Anonymity • Protecting data source (details will be discussed in later classes)

  31. Standardization of Sensor Networks • Zigbee Aliance • The ZigBee Alliance is an association of companies working together to enable reliable, cost-effective, low-power, wirelessly networked, monitoring and control products based on an open global standard. • Focus • Defining the network, security and application software layers    • Providing interoperability and conformance testing specifications   • Promoting the ZigBee brand globally to build market awareness   • Managing the evolution of the technology • Members: more than 100 companies

  32. Zigbee Specification (June 2005)

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