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A Methodology for the Deployment of Multi-Agent Systems on Wireless Sensor Networks. Richard Tynan, Antonio G. Ruzzelli, G.M.P. O’Hare Adaptive Information Cluster (AIC) Smart Media Institute Department of Computer Science University College Dublin Ireland. Summary.

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A Methodology for the Deployment of Multi-Agent Systems on Wireless Sensor Networks

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A methodology for the deployment of multi agent systems on wireless sensor networks l.jpg

A Methodology for the Deployment of Multi-Agent Systems onWireless Sensor Networks

Richard Tynan, Antonio G. Ruzzelli, G.M.P. O’Hare

Adaptive Information Cluster (AIC)

Smart Media Institute

Department of Computer Science

University College Dublin

Ireland


Summary l.jpg

Summary

  • Wireless sensor networks (WSNs)

  • Intelligent agents in WSNs

  • Methodology for agent deployment

    • Centralized approach at the BSs

    • Distributed approach at the BSs

    • Distributed approach at the sensor nodes

  • Methodological tool support

    • Data recorder/player

    • Sensor abstraction

    • New project wizard

  • Conclusion


Wireless sensor networks l.jpg

Wireless sensor networks

  • Few number of Base stations (BSs) and a large number of tiny devices (sensors)

  • WSNs are used for long unattended applications

  • Sensors are power constrained

  • Sensors collect data which are sent to one or more BSs

  • Communication are in Multi-hop fashion


Why agents in wsns l.jpg

Why agents in WSNs

  • Intelligent network management

  • To improve the adaptivity of the networks

  • To take local decision between neighbouring nodes rather than at the BS. Hence:

    • Energy saving

    • More accurate and faster response to network changes

    • Increase of preciseness of the action taken

Cons: Accommodate BDI agents is very challenging due to devices computationally limited


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Methodology phase 1: Centralised Base station implementation

  • A single agent placed at the BS

  • The agent receives raw data from nodes then analyse them

  • The agent identifies and solve anomalous behaviour of the network or part of it.

  • The agent communicate to the BS what action to take.


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Methodology phase 2: Distributed Base station implementation

  • The second phase transforms the centralised solution in a distributed agent-base implementation

  • The key point of this phase is to have a mapping between agents of a MAS and sensor nodes


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Agents-nodes mapping at the BS

  • One-to-One

    • Each node is controlled by one agent that deliberates accordingly

    • Nodes can be seen as agent perceptors

  • Many-to-One

    • Many agents map to an individual node

    • E.g. useful when nodes have several sensory modalities

  • One-to-Many

    • A single agent map to a group of neighbouring nodes

    • E.g. useful when decision may be taken by analysing a group of nodes locally placed


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Methodology phase 3: Distributed agents implementation

  • Agents on the nodes can be modelled through the agents at the BS

  • Hence, agents on the nodes can be easily debugged at the BS

  • The distributed implementation can be achieved by mapping the statements that govern the agents behaviour (such as commitment rules) to the language of the device .


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Methodological tool support 1:WSN data recorder/player

  • The recorder/player tool allows both to register parameters of an experiment and to log the data for replay later to similar experiments

    • It results in a big increase of experiments performed

    • Useful for comparison with similar experiments obtained by changing parameters

    • An experiment can be run several times for verification


Methodological tool support 2 observable network abstraction l.jpg

Methodological tool support 2:Observable network abstraction

  • It provides an abstraction to the sensor network by creating an array of sensor objects through the observer design pattern

  • The array is observed through a centralised solution

  • A received transmission is mapped to the required sensor object

    • It reduces the coupling between application layer and physical sensors.


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Methodological tool support 3:New project wizard

  • It has been created for new project in TinyOS

  • The IDE generates a shell of the application

  • Then a project directory and some files of the application are created

Code generated by the New Project Wizard for the Top Level Configuration file.


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Conclusion

  • We described an approach to deploying correct distributed algorithms on embedded devices

  • The approach tends to be more practical than other more formal and mathematical approaches studied.

  • The key of the approach lies on the one-to-one mapping of agents to nodes

  • The methodology allows the verification of the correctness of applications before the real deployment

  • While not so rigorous, it allows for a rapid deployment of a distributed algorithm already debugged for an high standard


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Thank you for your attention

  • Questions are welcome


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