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  • CORIE is a pilot environmental observation and forecasting system (EOFS) for the Columbia River. It integrates a real-time sensor network, a data management system and advanced numerical models. Through this integration, we seek to characterize and predict complex circulation and mixing processes in a system encompassing the lower river, the estuary and the near-ocean. The acquired knowledge is transformed into data products designed to provide objective insights on the spatial and temporal variability of the Lower Columbia River. As a scientific tool, CORIE is designed to advance the emerging field of environmental information systems, and the understanding of river-dominated estuaries and plumes. The scientific objectivity and breadth of products of CORIE also gives the region's natural resource management and regulation community powerful new planning and analysis tools to improve policies and decisions. Early applications of CORIE have, in particular, addressed issues combining salmon habitat and passage, hydropower management, navigation improvements and habitat restoration. These applications show that there is a role for objective science to engender consensus across agencies with conflicting mandates. They also suggest that coordinating resources of multiple users of a waterway in the development of a shared scientific infrastructure, readily adaptable to evolving needs, might be a practical way to develop affordable management tools. Rapidly advancing performance and declining costs of electronic and computer technology will soon make EOFS economically feasible. The experience of systems like CORIE will encourage and provide paradigms for the development of national and international networks of EOFS, to the benefit of science and society. CORIE is being developed at the OGI School of Science & Engineering of the Oregon Heath & Science University, by an interdisciplinary team under the scientific direction of Prof. António M. Baptista
  • Challenging Issues by Limited Computation and Data storage
  • Scalable Topology
  • Transcript

    • 1. Applications of Sensor Networks Chen, Weifeng Gong, Ying Liu, Xiaotao
    • 2. Outline <ul><li>Why sensor nets? </li></ul><ul><ul><li>Advantages </li></ul></ul><ul><ul><li>Applications </li></ul></ul><ul><li>Classifications of sensor nets </li></ul><ul><li>Challenging issues </li></ul><ul><ul><li>Common constraints </li></ul></ul><ul><ul><li>Application-specific constraints </li></ul></ul><ul><li>Discussions </li></ul>
    • 3. Outline <ul><li>Why sensor nets? </li></ul><ul><ul><li>Advantages </li></ul></ul><ul><ul><li>Applications </li></ul></ul><ul><li>Classifications of sensor nets </li></ul><ul><li>Challenging issues </li></ul><ul><ul><li>Common constraints </li></ul></ul><ul><ul><li>Application-specific constraints </li></ul></ul><ul><li>Discussions </li></ul>
    • 4. <ul><li>Intimate connection with its immediate environment. </li></ul>Advantages of Sensor Nets
    • 5. <ul><li>Intimate connection with its immediate environment. </li></ul><ul><li>No disturbance to environment, animals, plants, etc. </li></ul>Advantages of Sensor Nets (cont.)
    • 6. <ul><li>Intimate connection with its immediate environment. </li></ul><ul><li>No disturbance to environment, animals, plants, etc. </li></ul><ul><li>Avoid unsafe or unwise repeated field studies. </li></ul>Advantages of Sensor Nets (cont.)
    • 7. <ul><li>Intimate connection with its immediate environment. </li></ul><ul><li>No disturbance to environment, animals, plants, etc. </li></ul><ul><li>Avoid unsafe or unwise repeated </li></ul><ul><li>field studies. </li></ul><ul><li>Economical method for long-term data collection </li></ul><ul><ul><li>One deployment, multiple utilizations </li></ul></ul>Advantages of Sensor Nets (cont.)
    • 8. <ul><li>Habitat monitoring </li></ul><ul><li>Environmental observation and forecasting systems: Columbia River Estuary </li></ul><ul><li>Smart Dust </li></ul><ul><li>Biomedical sensors </li></ul>Applications of Sensor Nets
    • 9. <ul><li>Petrel habitat on Great Duck Island in Maine. </li></ul><ul><li>Questions to answer: </li></ul><ul><ul><li>Usage pattern of nesting burrows over the 24-72 hour cycle </li></ul></ul><ul><ul><li>Changes in the burrow and surface environmental parameters </li></ul></ul><ul><ul><li>Differences in the micro-environments with and without large numbers of nesting petrels </li></ul></ul><ul><li>Primitive requirement: no human disturbance. </li></ul>Habitat Monitoring
    • 10. Approach to habitat monitoring
    • 11. Estuarine Environmental Observation and Forecasting System <ul><li>Observation and forecasting system for the Columbia River Estuary </li></ul>
    • 12. CORIE Approach <ul><li>Real-time observations </li></ul><ul><ul><li>Estuarine and offshore stations </li></ul></ul><ul><li>Numerical modeling </li></ul><ul><ul><li>Produce forecast, hindcast of circulation </li></ul></ul><ul><li>Virtualization &amp; application </li></ul><ul><ul><li>Vessel survey, navigation </li></ul></ul><ul><ul><li>fishing, etc… </li></ul></ul>
    • 13. Smart Dust : Mote <ul><li>Tiny &amp; light-communication </li></ul>
    • 14. Military Applications of Smart Dust
    • 15. Biomedical Sensors <ul><li>Sensors help to create vision </li></ul>
    • 16. Outline <ul><li>Why sensor nets? </li></ul><ul><ul><li>Advantages </li></ul></ul><ul><ul><li>Applications </li></ul></ul><ul><li>Classifications of sensor nets </li></ul><ul><li>Challenging issues </li></ul><ul><ul><li>Common constraints </li></ul></ul><ul><ul><li>Application-specific constraints </li></ul></ul><ul><li>Discussions </li></ul>
    • 17. Classifications of Sensor Nets <ul><li>Sensor position </li></ul><ul><ul><li>Static (Habitat, CORIE, Biomedical) </li></ul></ul><ul><ul><li>Mobile (Smart Dust, Biomedical) </li></ul></ul><ul><li>Goal-driven </li></ul><ul><ul><li>Monitoring: Real-time/Not-real-time (Habitat, Smart Dust) </li></ul></ul><ul><ul><li>Forecasting (CORIE) </li></ul></ul><ul><ul><li>Function substitution (Biomedical) </li></ul></ul><ul><ul><li>… </li></ul></ul><ul><li>Communication medium </li></ul><ul><ul><li>Radio Frequency (Habitat, CORIE, Biomedical) </li></ul></ul><ul><ul><li>Light (Smart Dust) </li></ul></ul>
    • 18. Outline <ul><li>Why sensor nets? </li></ul><ul><ul><li>Advantages </li></ul></ul><ul><ul><li>Applications </li></ul></ul><ul><li>Classifications of sensor nets </li></ul><ul><li>Challenging issues </li></ul><ul><ul><li>Common constraints </li></ul></ul><ul><ul><li>Application-specific constraints </li></ul></ul><ul><li>Discussions </li></ul>
    • 19. Common Challenging Issues <ul><li>Limited computation and data storage </li></ul><ul><li>Low power consumption </li></ul><ul><li>Wireless communication </li></ul><ul><ul><li>Medium, ad hoc vs. infrastructure, topology and routing </li></ul></ul><ul><li>Data-related issues </li></ul><ul><li>Continuous operation </li></ul><ul><li>Inaccessibility – network adjustment and retasking </li></ul><ul><li>Robustness and fault tolerance </li></ul>
    • 20. Application-specific Constraints <ul><li>Material Constraints </li></ul><ul><ul><li>Bio-Compatibility </li></ul></ul><ul><ul><li>Inconspicuous </li></ul></ul><ul><ul><ul><li>Imitative to environment </li></ul></ul></ul><ul><ul><ul><li>Detect-proof: e.g. stealth flight </li></ul></ul></ul><ul><li>Secure Data Communications </li></ul><ul><li>Regulatory Requirements – such as FDA </li></ul>
    • 21. Limited Computation and Data Storage <ul><li>Sensor design </li></ul><ul><ul><li>Multi-objective sensors and single (a few)-objective sensors. </li></ul></ul><ul><li>Cooperation among sensors </li></ul><ul><li>Data aggregation and interpretation </li></ul>
    • 22. Low Power Consumption <ul><li>Low power functional components </li></ul><ul><li>Power-manageable components </li></ul><ul><ul><li>Several functional state (low state-transition overhead) </li></ul></ul><ul><ul><ul><li>Deep-sleep, Sleep, On </li></ul></ul></ul><ul><ul><ul><li>Provide different QoS with different power consumption. </li></ul></ul></ul><ul><li>Power Management </li></ul><ul><ul><li>Power measurement </li></ul></ul><ul><ul><li>Power budget allocation </li></ul></ul><ul><ul><li>Control transitions between different power states. </li></ul></ul>
    • 23. Wireless Communication <ul><li>Communication mediums </li></ul><ul><ul><li>Radio Frequency: Habitat monitoring, Biomedical sensors and CORIE estuarine observation </li></ul></ul><ul><ul><li>Light (active and passive): Smart Dust </li></ul></ul><ul><li>Ad hoc versus infrastructure modes </li></ul><ul><li>Topology </li></ul><ul><li>Routing </li></ul>
    • 24. Smart Dust: Passive Transmitters Asymmetric Link assumed: high power laser emit from BS, with larger scale imaging array Downlink Laser Uplink CCD Corner-Cube Uplink DataIn Data Image Sensor Retroreflector DataIn Photo- Downlink DataOut detector Base-StationTransceiver DustMote Signal Selection and Processing Uplink Data ... Out N Out 1 Array UnmodulatedInterrogation ModulatedReflected Lens Lens ModulatedDownlinkDataor BeamforUplink BeamforUplink
    • 25. Smart Dust: Active Transmitter (cont.) <ul><li>BS uses CCD or CMOS camera (operate at up to 1 Mbps) </li></ul><ul><li>Using multi-hop routing, not all dust motes need LoS to BS </li></ul>Transmitter Radiant Intensity Receiver Light Collection Area Base Transceiver Station Dust Mote Dust Mote Dust Mote Wall
    • 26. Smart Dust: Active Transmitter Two-axis beam steering assembly Active dust mote transmitter <ul><ul><li>Beams have divergence &lt;&lt; 1º </li></ul></ul><ul><ul><li>Steerable over a full hemisphere </li></ul></ul>
    • 27. Ad hoc vs. Infrastructure Modes <ul><li>Sensor - Sensor communication: </li></ul><ul><ul><li>Short distance </li></ul></ul><ul><ul><li>Ad hoc </li></ul></ul><ul><li>Sensor - Base station communication: </li></ul><ul><ul><li>Long distance sensor to base station communication </li></ul></ul><ul><ul><li>Infrastructure </li></ul></ul>
    • 28. Wireless Communication: Topology <ul><li>Fixed topology </li></ul><ul><ul><li>Tree based </li></ul></ul><ul><ul><li>Cluster based </li></ul></ul><ul><li>Dynamic topology - mobility </li></ul><ul><ul><li>Ad hoc </li></ul></ul><ul><ul><li>Infrastructure </li></ul></ul><ul><ul><li>Mixed </li></ul></ul>
    • 29. Research on Fixed Topologies <ul><li>Vary # of neighbors </li></ul><ul><li>Trade-offs exist </li></ul><ul><ul><li>Number of hops </li></ul></ul><ul><ul><li>Number of receivers </li></ul></ul><ul><ul><li>Amount of contention </li></ul></ul><ul><li>Evaluate power usage </li></ul><ul><li>Test power-aware routing </li></ul><ul><li>Results: </li></ul><ul><ul><li>Power-aware routing reduces power usage </li></ul></ul><ul><ul><li>3D is better than 2D </li></ul></ul>
    • 30. Research on Fixed Topologies (cont.) Cluster-based Tree-based Cluster-based approach provides better energy-efficiency than the tree-based approach.
    • 31. Wireless Communication: Routing <ul><li>Route discovery </li></ul><ul><li>Redundancy discovery </li></ul><ul><li>Failure detection and recovery </li></ul><ul><li>Distributed and localized </li></ul><ul><ul><li>Avoid single-point failure </li></ul></ul><ul><ul><li>Avoid bottleneck </li></ul></ul><ul><li>Energy-efficient </li></ul>
    • 32. Energy-Efficient Routing Protocol <ul><li>Routing protocol metrics: </li></ul><ul><ul><li>Traditional: packet loss, routing message overhead, routing length </li></ul></ul><ul><ul><li>New metric: energy consumption: ,  =2~4 </li></ul></ul><ul><ul><li>Imagine: </li></ul></ul>5 S T M 5 9
    • 33. Data-related issues <ul><li>Trade-off between latency and energy </li></ul><ul><ul><li>Real-time </li></ul></ul><ul><ul><li>Periodic </li></ul></ul><ul><li>Data representation </li></ul><ul><ul><li>Raw/Compressed data </li></ul></ul><ul><ul><li>Sampling Value: Absolute/Relative </li></ul></ul><ul><li>Error calibration </li></ul><ul><ul><li>No access to real values </li></ul></ul><ul><ul><li>Inferred from other sensors </li></ul></ul>
    • 34. Continuous Operation <ul><li>Long-term data collection </li></ul><ul><li>Renewable power source. </li></ul><ul><ul><li>Solar energy </li></ul></ul><ul><ul><li>Mechanical vibrations </li></ul></ul><ul><ul><li>Radio-Frequency inductance </li></ul></ul><ul><ul><li>Infrared inductance </li></ul></ul>
    • 35. Inaccessibility <ul><li>Sensor location </li></ul><ul><ul><li>Embedded environment </li></ul></ul><ul><ul><li>Avoid disturbance to sensing objects </li></ul></ul><ul><li>Network adjustment </li></ul><ul><li>Network retasking </li></ul>
    • 36. Robustness and Fault Tolerance <ul><li>Self-adaptive sensors: </li></ul><ul><ul><li>Adapted to the environment changes. </li></ul></ul><ul><ul><li>Adapted to the power change. </li></ul></ul><ul><li>Distributed network: </li></ul><ul><ul><li>Each sensor operate autonomously from neighbors. </li></ul></ul><ul><ul><li>Overlapped services area. </li></ul></ul><ul><ul><li>No single point of failure. </li></ul></ul><ul><li>Health and status monitoring </li></ul><ul><ul><li>E.g. reporting power along data transmission </li></ul></ul>
    • 37. Outline <ul><li>Why sensor nets? </li></ul><ul><ul><li>Advantages </li></ul></ul><ul><ul><li>Applications </li></ul></ul><ul><li>Classifications of sensor nets </li></ul><ul><li>Challenging issues </li></ul><ul><ul><li>Common constraints </li></ul></ul><ul><ul><li>Application-specific constraints </li></ul></ul><ul><li>Discussions </li></ul>
    • 38. Discussions <ul><li>Unique solution to all applications exists? </li></ul><ul><li>Most important considerations in designing: </li></ul><ul><ul><li>Cost? </li></ul></ul><ul><ul><li>Resource allocation? </li></ul></ul><ul><ul><li>Manageability? </li></ul></ul><ul><ul><li>Timeliness? </li></ul></ul><ul><ul><li>Retasking? </li></ul></ul><ul><ul><li>… </li></ul></ul><ul><li>Scalability? </li></ul><ul><ul><li>Millions of sensor nodes? </li></ul></ul><ul><li>Next generation sensor nets? </li></ul>
    • 39. The End Thank you

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