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Topic 3: Sensor Networks and RFIDs

Topic 3: Sensor Networks and RFIDs

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Topic 3: Sensor Networks and RFIDs

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  1. Northwestern University MITP 491: Selected Topics in Information Technology Topic 3: Sensor Networks and RFIDs Part 6 Instructor: Randall Berry e-mail: rberry@ece.northwestern.edu

  2. Networking Issues • MAC layer issues • Topology control • Routing

  3. Routing • In multi-hop networks, a routing algorithm needed to specify how packets reach destinations.

  4. Routing Challenges • Algorithm must be adaptive to topology changes. • Due to mobility, node failures, etc. • Limiting routing overhead is required due to energy considerations. • Nodes may also have limited memory for routing tables.

  5. Routing considerations • Types of flows: • Unicast, multicast, broadcast, geocast. • Type of topology: • Tree, mesh. • Routing metrics: • Shortest paths, minimum energy, maximum lifetime. • Availability of location information.

  6. Unicast Routing(Mesh topology) • Many approaches: • Flooding, Gossiping. • Proactive routing (Table-based). • Reactive routing (on-demand). • Geographic routing.

  7. Flooding • Simplest type of routing • Send any new packet to all neighbors (except one received from) • “Wireless broadcast advantage” can help. • Usually some type of expiration for each packet. • Minimal memory requirements/control traffic. • But excessive number of transmissions to reach destination. • Topology control can help here

  8. Flooding/Gossiping • Flooding can be useful for broadcast data. • Still can result in excessive transmissions/collisions. • Gossip algorithms attempt to reduce this • Two variations: • Randomly pick one node to forward to. • Each node only forwards a new packet with some probability p. • Cost?

  9. Proactive/Reactive Routing • Both require nodes to keep a routing table. • Difference is when table is updated. • Proactive schemes attempt to always have an up-to-date table. • Reactive schemes only update tables “on demand” i.e. when traffic to send. • Trade-offs?

  10. Proactive/Reactive Routing • The routing algorithms used in the internet are an example of proactive routing. • Periodically routers exchange distance vectors or link states. • Every router has a routing table with up-to-date routes. • An example of a reactive protocol is the AODV (Ad hoc On demand Distance Vector) protocol • routing option for Zigbee mesh networks. • Various hybrids also exist.

  11. AODV • In AODV nodes do not exchange any routing info. • To establish a route to a new destination a node broadcasts a route request (RREQ) packet to all neighbors. • RREQ contains destination address, source address, hop count, broadcast id, and source and destination sequence numbers.

  12. AODV • When node receives a RREQ: • If already seen – does nothing. • If new and no route to destination - increments hop count, forwards RREQ, and stores routing entry to source. • If knows route to destination – then responds with a route reply (RREP) containing source/dest id, hop cnt and lifetime. • Route replies return along reverse path – nodes update routing tables to destination. • After “lifetime” routes will be dropped from memory.

  13. AODV Variations: • Route maintenance: neighbors send “hello” messages and propagate route error messages when links break. • Other route metrics:replace hop cnt with some other metrics. • Limited flooding:include max. hop cnt in RREQ.

  14. Geographic routing • When nodes have location-information can use this to facilitate routing. • Information may be from GPS, in-network localization, or given at deployment. • Geographic routing algorithms route only using location-information (I.e. no node ID’s) • Natural correspondence to location-based queries.

  15. Geographic routing • Simplest approach – “greedy forwarding” • Always send packet to neighbor who is closest to the destination. • Several variants: • E.g. nearest neighbor with forward progress. • Problem?

  16. Geographic routing • Getting around “dead-ends:” • “Face routing:” use a right-hand rule when stuck. • Greedy perimeter stateless routing(GPSR) is an algorithm that uses these ideas. • Greedy routing until “stuck” • Then face routing until “un-stuck”

  17. Data centric routing • In many sensor network applications do not want to send data to specific nodes, but rather to any node that knows “x”. • Traditional approach to such problems. • Add “higher layer names” for data of interest. • Somehow bind those names to the nodes which have that data (e.g. thru a directory service) • This leads to several levels of indirection, each which add overhead to the sensor network. • Moreover, since most sensor networks are application specific, it is not clear this is needed.

  18. Data-centric routing • Main idea: implement network operations directly using content names. • Requires having a system for content-based addressing. • E.g. [Temperature, location, time]. • Need mechanisms for advertising & requesting content • Publish/subscribe model • Push vs. pull.

  19. Directed Diffusion • One broad data centric routing approach is directed diffusion. • Inspired by ants. • “Pull” algorithm – sinks transmit interests for certain types of data. • Interests are flooded through network. • Other nodes cache the interest, and create a gradient towards the source • direction plus value.

  20. Directed Diffusion • When a node obtains data that matches an interest it sends it along gradient direction • Rate (probability) proportional to gradient value. • Sink reinforces particular route(s) • Increase rate of gradient • Reinforcements propagate back to source.

  21. Directed Diffusion • Quite general algorithm. • Probabilities can depend on energy/delay. • Multi-path version possible. • Also “push”-based versions.

  22. Outline • Discuss applications in HW. • Loose ends from last time • Networking issues: • MAC protocols • Topology formation • Routing • Security • Future trends

  23. Security Concerns • Access control • Message integrity • Message confidentiality • Replay protection • Denial of service protection • Jamming, energy depletion, etc.

  24. Security Concerns • Access control • Message integrity • Message confidentiality • Replay protection • Denial of service protection Addressed as options in 802.15.4/Zigbee

  25. Zigbee Security solutions • Access control • coordinator maintains access list. • Message integrity. • Include a message authentication code with each (MAC layer) packet. • Cryptographic checksum • 4/8/16 byte options.

  26. Zigbee Security solutions • Message confidentiality. • Encrypt message. • Replay protection. • Include a sequence number in each packet.

  27. Today • Discuss applications in HW. • Loose ends from last time • Networking issues: • MAC protocols • Topology formation • Routing • Security • Future trends

  28. Future Trends • Markets • Challenges

  29. Markets “By 2008, there could be 100 million wireless sensors in use, up from about 200,000 today. The worldwide market for wireless sensors, will grow from $100 million this year to more than $1 billion by 2009.” – Harbor research, 2006

  30. Markets Many companies are positioning themselves at several different points in the sensor network “value chain”: • Component suppliers (e.g. chips, mini-controllers, sensors) • Freescale, Intel, TI (Chipcon), …. • Network technology companies (e.g. motes, access points) • Crossbow, Millennial Nets, Dust Networks,… • System integrators (installation services, applications) • Intel, IBM, HP,… • Data management/analysis (what to do with all this data) • Oracle, SAP, Microsoft,… • Also Companies with specialized Apps. • Home automation, toys, …

  31. Markets • RFID is already seeing widespread deployment. • Some Zigbee products are also becoming available for applications such as home automation. • Markets for other sensor net applications are also emerging. • However, some of the more exotic apps are still not feasible. • Large deployments of low power nodes, with multi-hop routing and long-lifetimes.

  32. Challenges • Reliability (lifetimes). • Made a lot of progress here, but improvements still needed in some areas. • As we have seen, some will come from Moore’s law - others will require new solutions. • Security/Privacy • Societal implications of widespread use of sensors/RFIDs • Privacy/regulation/societal acceptance.