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Agent Technologies for Sensor Networks<br />Reference:                    Alex Rogers and Nicholas R. Jennings,  Universit...
Introduction<br />Wireless Sensor Network<br />Way of wide-area monitoring<br />Work with environmental, security, and mil...
Challenges<br />Wireless Sensor Network<br />Collect data over extended periods of  time<br />Deployed  in inhospitable en...
Overcomes<br />Multiagent Systems Need<br />Extensive set of  formalisms, algorithms, and methodologies<br />Mapping from ...
New Synthesis<br />Synthesis Has Succeeded <br />Efficient decentralized coordination  algorithms <br />Sensor-agent  plat...
Agent-Based Decentralized Coordination<br />Coordination Might Include <br />Routing data through the network<br />Choosin...
Agent-Based Decentralized Coordination<br />Proposed Algorithms <br />Agent update their state for its own not globally<br...
Figure 1. Hardware implementation of the max-sum algorithm <br />and the graph-coloring benchmark problem using the Texas ...
Deploying Sensor Agentsin the Field<br /><ul><li>Field deployment presents significant additional challenges
The CNAS has created a agent-based sensor network
Each agent decides what and when to perform the activities
Sharing of information is better to inform high-level operational  decision  making</li></ul>9<br />Md. Merazul Islam, CSE...
Figure 2. A CNAS sensor agent at the <br />2006 Patriot Exercise at Fort McCoy, <br />Wisconsin, deployed to collect real-...
Information Agents for Pervasive Sensor Networks<br />Agents Must be Able  to <br />Handle missing or delayed data<br />De...
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0507036 (2)

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0507036 (2)

  1. 1. Agent Technologies for Sensor Networks<br />Reference: Alex Rogers and Nicholas R. Jennings, University of Southampton<br />Daniel D. Corkill, University of Massachusetts Amherst<br />IEEE Intelligent Systems, March-April 2009<br />Presented By: Md. Merazul Islam<br />0507036<br />Dept. of CSE, KUET<br />
  2. 2. Introduction<br />Wireless Sensor Network<br />Way of wide-area monitoring<br />Work with environmental, security, and military scenarios<br />Consist of small, battery-powered devices<br />Connected through a wireless communication network<br />Faces some challenges<br />2<br />Md. Merazul Islam, CSE, KUET<br />
  3. 3. Challenges<br />Wireless Sensor Network<br />Collect data over extended periods of time<br />Deployed in inhospitable environments<br />Replacing batteries is impossible<br />Goals not achieve<br />Sensors don’t share their sensing actions<br />Network don’t adapt responses in a dynamically changing environment<br />3<br />Md. Merazul Islam, CSE, KUET<br />
  4. 4. Overcomes<br />Multiagent Systems Need<br />Extensive set of formalisms, algorithms, and methodologies<br />Mapping from sensor to agent<br />Use of more low power resources<br />Reliable hardware and communication<br /> Rather than we need A New Synthesis<br />4<br />Md. Merazul Islam, CSE, KUET<br />
  5. 5. New Synthesis<br />Synthesis Has Succeeded <br />Efficient decentralized coordination algorithms <br />Sensor-agent platforms in the field<br />Intelligent agents<br />These three examples are Proved & Evaluated by the researchers in real, hostile environment<br />5<br />Md. Merazul Islam, CSE, KUET<br />
  6. 6. Agent-Based Decentralized Coordination<br />Coordination Might Include <br />Routing data through the network<br />Choosing appropriate sampling rates of sensors<br />Coordination Should Performed<br />No central point of failure exits<br />Computation must shared over the distributed resources<br />Number of devices in the network increases<br />6<br />Md. Merazul Islam, CSE, KUET<br />
  7. 7. Agent-Based Decentralized Coordination<br />Proposed Algorithms <br />Agent update their state for its own not globally<br />Max-sum algorithm used to solve it<br />Requires less computational and communication resources<br />Generates good solutions applied to cyclic graphs<br />Researchers have implemented it in hardware<br />7<br />Md. Merazul Islam, CSE, KUET<br />
  8. 8. Figure 1. Hardware implementation of the max-sum algorithm <br />and the graph-coloring benchmark problem using the Texas <br />Instruments CC2430 System-on-Chip. The seven-segment display <br />indicates the number of neighbors that each sensor has located, <br />and the three LEDs indicate their respective sensor’s chosen color.<br />8<br />Md. Merazul Islam, CSE, KUET<br />
  9. 9. Deploying Sensor Agentsin the Field<br /><ul><li>Field deployment presents significant additional challenges
  10. 10. The CNAS has created a agent-based sensor network
  11. 11. Each agent decides what and when to perform the activities
  12. 12. Sharing of information is better to inform high-level operational decision making</li></ul>9<br />Md. Merazul Islam, CSE, KUET<br />
  13. 13. Figure 2. A CNAS sensor agent at the <br />2006 Patriot Exercise at Fort McCoy, <br />Wisconsin, deployed to collect real-time <br />weather data at a landing strip. (photo <br />courtesy of the US Air Force)<br />10<br />Md. Merazul Islam, CSE, KUET<br />
  14. 14. Information Agents for Pervasive Sensor Networks<br />Agents Must be Able to <br />Handle missing or delayed data<br />Detect faulty sensors<br />Fuse noisy measurements from several sensors<br />Efficiently manage bandwidth<br />Predict both the value of missing sensor<br />A live implementation of this prototype agent is currently available<br />11<br />Md. Merazul Islam, CSE, KUET<br />
  15. 15. Figure 3. The Bramble Bank weather Station, located in the Solent. <br />Figure 4. Screenshot of an information agent. A live implementation is available at <br />www.aladdinproject.org/situation<br />12<br />Md. Merazul Islam, CSE, KUET<br />
  16. 16. Conclusion<br />The examples described here illustrate that even experimental sensor agent technology has become sufficiently reliable.<br />Doing so will no doubt introduce novel challenges<br />13<br />Md. Merazul Islam, CSE, KUET<br />
  17. 17. Thanks to all<br />14<br />Md. Merazul Islam, CSE, KUET<br />

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