AGENT TECHNOLOGIES FOR SENSOR NETWORKS

Reference: Alex Rogers and Nicholas R. Jennings, University of Southampton

Daniel D. Corkill, University of Massachusetts Amherst

IEEE Intelligent Systems, March-April 2009

Presented By: Md. Merazul Islam0507036

Dept. of CSE, KUET

Md. Merazul Islam, CSE, KUET 2

INTRODUCTION

• Wireless Sensor Network– Way of wide-area monitoring– Work with environmental, security, and military

scenarios– Consist of small, battery-powered devices– Connected through a wireless communication

network– Faces some challenges

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CHALLENGES

• Wireless Sensor Network– Collect data over extended periods of time– Deployed in inhospitable environments– Replacing batteries is impossible

• Goals not achieve– Sensors don’t share their sensing actions– Network don’t adapt responses in a dynamically

changing environment

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OVERCOMES

• Multiagent Systems Need– Extensive set of formalisms, algorithms, and

methodologies– Mapping from sensor to agent– Use of more low power resources– Reliable hardware and communication

Rather than we need A New Synthesis

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NEW SYNTHESIS

• Synthesis Has Succeeded 1. Efficient decentralized coordination algorithms 2. Sensor-agent platforms in the field3. Intelligent agents

These three examples are Proved & Evaluated by the researchers in real, hostile environment

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AGENT-BASED DECENTRALIZED COORDINATION

• Coordination Might Include – Routing data through the network– Choosing appropriate sampling rates of sensors

• Coordination Should Performed1. No central point of failure exits2. Computation must shared over the distributed

resources3. Number of devices in the network increases

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AGENT-BASED DECENTRALIZED COORDINATION

• Proposed Algorithms – Agent update their state for its own not globally– Max-sum algorithm used to solve it– Requires less computational and communication

resources– Generates good solutions applied to cyclic graphs

Researchers have implemented it in hardware

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Figure 1. Hardware implementation of the

max-sum algorithm and the graph-coloring

benchmark problem using the Texas

Instruments CC2430 System-on-Chip. The

seven-segment display indicates the number

of neighbors that each sensor has located, and the three LEDs

indicate their respective sensor’s

chosen color.

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DEPLOYING SENSOR AGENTSIN THE FIELD

o Field deployment presents significant additional challenges

o The CNAS has created a agent-based sensor network

o Each agent decides what and when to perform the activities

o Sharing of information is better to inform high-level operational decision making

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Figure 2. A CNAS sensor agent at the 2006 Patriot Exercise at Fort McCoy, Wisconsin, deployed to collect real-time weather data at a landing strip. (photo courtesy of the US Air Force)

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INFORMATION AGENTS FOR PERVASIVE SENSOR NETWORKS

• Agents Must be Able to – Handle missing or delayed data– Detect faulty sensors– Fuse noisy measurements from several sensors– Efficiently manage bandwidth– Predict both the value of missing sensor

A live implementation of this prototype agent is currently available

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Figure 3. The Bramble Bank weather Station, located in the Solent.

Figure 4. Screenshot of an information agent. A live

implementation is available at www.aladdinproject.org/situation

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CONCLUSION

• The examples described here illustrate that even experimental sensor agent technology has become sufficiently reliable.

• Doing so will no doubt introduce novel challenges

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Thanks to all