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

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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  1. 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

  2. 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

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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 .

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. Thank you for your attention • Questions are welcome

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