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Applications and communication patterns for WSN

Applications and communication patterns for WSN. N. Reijers. Consensus day TU Delft February 7, 2003. WSN applications and traffic. MAC simulation requires generating realistic WSN traffic Routing Data aggregation OS Expected to have special characteristics. Application scenarios.

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Applications and communication patterns for WSN

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  1. Applications and communication patternsfor WSN N. Reijers Consensus day TU Delft February 7, 2003

  2. WSN applications and traffic • MAC simulation requires generating realistic WSN traffic • Routing • Data aggregation • OS • Expected to have special characteristics

  3. Application scenarios • Intruder detection • Forest fire detection • Cattle herd • Battle field • Fire rescue • Environmental monitoring • Condition based maintenance • Airconditioning sensors

  4. 3 types of applications Detection Tracking Active Passive Monitoring Push Pull Communication Event Periodic/event Periodic Query/response Application types

  5. Example:Sheep tracking • Farmers want to know: • Rough location of their sheep • When a sheep wanders off from the herd • When a sheep is lying on its back • Sensor nodes spread throughout the meadow • Sheep carry a node that periodically sends a beacon pulse

  6. Sheep tracking approaches • Raw data to sink • Very inefficient • Active node • Cheap in terms of communication • Rough location estimate • Local triangulation • More expensive in terms of communication • More accurate location

  7. Active node Sink Sheep

  8. Active node Sheep Sink

  9. Local triangulation Sheep Sink

  10. WSN application characteristics • Activity is often very localized both in space and time • High latency is tolerable • Available bandwidth >> required bandwidth • Messages • local or node->sink • sink->node are rare

  11. Application model • Capture charateristics in application scenarios • Generate traffic which is typical for WSN • Scenario description • Network description • Traffic generation • Active areas

  12. Network model • Number of nodes • Placement of nodes • Random • Grid • Radio range • Number of sinks • Placement of sinks • Center / edge / corner

  13. Traffic generation (1) • Generate random messages • Rate (msgs/sec) • Type, selected according to given ratio • Local broadcast • Local unicast • Node -> sink • Sink -> node • Sink -> all 86 38 % 50 % 12 % 0 % 0 %

  14. Traffic generation (2) • For each message type, specify • Message size • Allowed latency • For node->sink messages specify aggregation type • None • Concatenation • Averaging

  15. Active areas • Active areas appear randomly • Rate (new areas/sec) • Avg lifetime • Avg size • 2nd set of parameters for active areas • Traffic generated for active areas is added to normal traffic

  16. Conclusion • Specific characteristics of WSN applications • localized activity • latency • available bandwidth >> required bandwidth • messages • local or node->sink • sink->node are rare • Traffic generation algorithm to model these

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