International Conference on Recent Trends in Information Technology and Computer Science |
Foundation of Computer Science USA |
ICRTITCS - Number 1 |
March 2012 |
Authors: Pranita M. Potey, Naveeta Kant |
413e5207-d4aa-40f1-bfa6-b67c7454c9a8 |
Pranita M. Potey, Naveeta Kant . Authentication based Hop Count Clustering Algorithm in Mobile Adhoc Network. International Conference on Recent Trends in Information Technology and Computer Science. ICRTITCS, 1 (March 2012), 13-17.
Recently, extensive research efforts have been devoted to the design of clustering algorithms to organize all the hosts in a mobile ad hoc network into a clustering architecture. Clustering is an important research topic because clustering makes it possible to guarantee basic levels of system performance, such as throughput and delay, in the presence of both mobility and a large number of mobile. MANETS have a limitation of battery power, cluster formation is expensive in terms of power depletion of nodes. This is due to the large number of messages passed during the process of cluster formation. A large variety of approaches for ad hoc clustering have been presented, whereby different approaches typically focus on different performance metrics. In this paper, we use the hop count based approach for binding a node to a cluster. We minimize the explicit message passing in cluster formation. We also used the route message of a proactive routing protocol for keeping track of nodes in cluster. Our scheme also involves low latency in the cluster formation phase. In addition, we choose the cluster gateway during cluster formation avoiding the need to explicitly discover the gateways, thus reducing further the transmission overheads. In this paper, we will propose an efficient clustering algorithm that can establish a stable clustering architecture by keeping a host with weak battery power from being elected as a cluster head. Addition to this we will focus authentication of node. Computer simulations show that clustering architectures generated by our clustering algorithm are more stable than those generated by other clustering algorithms.