Adaptive clustering based on auto: learning algorithm

Authors:
Anis Ben Arbia;Habib youssef
Affiliations:
Prince Research Unit, ISITC Hammam Sousse, University of Sousse, Tunisia;Prince Research Unit, ISITC Hammam Sousse, University of Sousse, Tunisia
Venue:
VECoS'08 Proceedings of the Second international conference on Verification and Evaluation of Computer and Communication Systems
Year:
2008

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Abstract

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.