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Integration of Sensor Networks with Mobile Devices

Computer Science Department University College London. Integration of Sensor Networks with Mobile Devices. Vladimir Dyo November 22, 2005. Outline. Introduction Problem and Motivation Isolating Problems Expected Contribution Initial Research Results Conclusion.

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Integration of Sensor Networks with Mobile Devices

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  1. Computer Science Department University College London Integration of Sensor Networks with Mobile Devices Vladimir Dyo November 22, 2005

  2. Outline • Introduction • Problem and Motivation • Isolating Problems • Expected Contribution • Initial Research Results • Conclusion

  3. Data Dissemination in SensorNets • The Concept • Sensors, Sinks • Tasks: Dissemination, Aggregation, Streaming • Limitation: Energy, Low Reliability

  4. Current Research • Infrastructure • Routing • GPSR • Clustering • LEECH • Data Dissemination and Aggregation protocols • Directed Diffusion, TAG, Synopsys Diffusion • Middleware • Milan, TinyLime, Slime, EnviroTrack

  5. Problem - I • Existing solutions work with static sinks: • Very strong assumption • Not Realistic • Not Energy Efficient • No Coverage • Examples: TinyDB, Cougar

  6. Problem - II: Example • Static collection: • Energy consumption • Congestion • Reliability • Not practical Suggested Approach: Mobile Collection

  7. Solution – Mobile Collection • Technical Advantages • Coverage, energy, disconnected operations, flexibility • Application Potential • Environmental monitoring, industrial and pervasive applications • Not Well Researched • M. Batalin, “Coverage, Exploration and Deployment by a Mobile Robot and Communication Network” • A. Chakrabarty, “Exploiting Predictable Observer Mobility For Power Efficient Sensor Network Configuration” • “S. Bhattacharya, Energy-conserving Data Placement and Asynchronous Multicast in WSN”

  8. Isolating Problems • Protocol Support • Mobile Data Collection. Routing Data towards a mobile collector • Spatial Queries and Distributed Index • select locations where (temp > 30) OR (humidity > 0.4) within 30km from (X,Y) • Middleware • Defining Primitives • Implementing Protocols

  9. Expected Contribution • Protocols • Data Collection Protocol for Mobile Collectors • Distributed Index for Spatial Queries in Sensor Networks • Middleware for integration of sensor networks with mobile devices • Architecture • Primitives • Implementation

  10. Evaluation • Data Collection Protocol: • Performance analysis in ns-2 simulator • Critical Metric – total communication overhead • Real traces from other projects • Implementation in TSky motes • Middleware • Implementation • Real Deployment • Climate and wildlife monitoring (in collaboration with Oxford zoologists) • Micro-climate monitoring (UCL campus)

  11. Initial Results • Adaptive Distributed Indexing for Spatial Queries in Sensor Networks. • V. Dyo and C. Mascolo. In IEEE Proceedings of 8th International Workshop on Mobility in Databases and Distributed Systems (co-located with DEXA05). August 2005, Copenhagen, Denmark. IEEE Computer Society Press

  12. Proactive + Reactive Mode 600 query/hour Total: 3601 Total: 2400 Proactive = 1 Proactive = 3600 Total: 1201 Reactive = 1200 Reactive = 1200

  13. Future work on Index • Data Resolution • High update rates  High Power Consumption • Low response • Low latency  High Power Consumption • Trade-off between: • Data resolution/response latency • Total energy consumption

  14. Conclusion • Interesting problem • Isolating issues • Initial results

  15. Questions • Vladimir Dyo • v.dyo@cs.ucl.ac.uk

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