Relative Weight Based Clustering in Mobile Ad Hoc Networks

Efficient and stable clustering always depends on choosing an appropriate cluster head in the network. A novel clustering protocol is proposed that employs a powerful analytical hierarchy process methodology, a mathematical model to compute relative weights for all the mobile nodes to choose appropriate cluster heads in the network. The five crucial factors of the mobile nodes are identified that influence the choosing of cluster heads. This novel clustering algorithm enhances the stability of the network to a great extent by reducing cluster head changes. Simulation results show that study of various performance metrics and it is compared with previous clustering algorithm.

[1]  Sajal K. Das,et al.  WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks , 2002, Cluster Computing.

[2]  Winston Khoon Guan Seah,et al.  Mobility-based d-hop clustering algorithm for mobile ad hoc networks , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[3]  Peter Han Joo Chong,et al.  An efficient clustering scheme for large and dense mobile ad hoc networks (MANETs) , 2006, Comput. Commun..

[4]  Winston Khoon Guan Seah,et al.  Performance analysis of mobility-based d-hop (MobDHop) clustering algorithm for mobile ad hoc networks , 2006, Comput. Networks.

[5]  Prithwish Basu,et al.  A mobility based metric for clustering in mobile ad hoc networks , 2001, Proceedings 21st International Conference on Distributed Computing Systems Workshops.

[6]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .