UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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.

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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.

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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.

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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.

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP 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

UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP Thank you for your attention Questions are welcome