Associativity Based Mobility-Adaptive K-Clustering in Mobile Ad-Hoc Networks

• Published in: Intelligent Information Technology pp. 160 - 168
• Main Authors: Jayakumar, C., Chellappan, C.
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 01.01.2004; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Cluster Head; Computer science; control theory; systems; Dynamic Source Route; Exact sciences and technology; Learning and adaptive systems; Member Node; Neighbor Table; Route Protocol; Cluster analysis; Mobility; Routing; Maintenance; Distributed system; Adaptive method; Routing algorithm; Leader election; Classification; Wireless network; Ad hoc network; Associativity; Artificial intelligence; Service quality; Mobile computing
• ISBN: 9783540241263; 3540241264
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-30561-3_17

In this paper we propose Clustering technique provides a solution to support QoS in ad hoc networks. For the effective functioning of cluster based routing algorithms, the clusters must be long-lived and stable. The proposed scheme considers the spatial and temporal stability of the nodes. The node elected as the clusterhead is such that it has maximum associativity as well as satisfies a minimum connectivity requirement. Effective work has been done for Cluster Reorganization. Cluster Head Re-election is periodically done so that the cluster head is centered in a cluster. Cluster management will be effective, since the cluster heads are elected based on various parameters like processing capabilities, speed of the node, number of neighbor nodes and associativity with the neighbor nodes. Though overhead is incurred initially due to cluster setup, cluster maintenance will be easier in the long run. Ultimately routing efficiency will increase due to long-lived clusters and reduced control packets.