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    Adaptive Clustering Based on Auto - Learning Algorithm

    Second International Workshop on Verification and Evaluation of Computer and Communication Systems (VECoS 2008)

    Leeds, UK, 2 - 3 July 2008


    Anis Ben Arbia and Habib Youssef


    This paper introduces an adaptive clustering model for wireless ad hoc networks based on Auto - Learning Algorithm (ALA). ALA allows a dynamic decomposition of the network into a virtual clusters view based on communication patterns of the mobile nodes. We consider a cluster as an Interest Group (IG) whose member nodes have common interactions. ALA is based on two types of events, New Route Events (NRE) and Route Failure Events (RFE). In this work, ALA is integrated into the well known routing protocol AODV. The adaptive version of AODV is referred to as A²ODV (Adaptive AODV). Simulation results show that A²ODV outperforms AODV with respect to packet delivery ratio, overhead, throughput, and route stability.


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