Study of different mobility models and clustering algorithms like weighted clustering algorithm (WCA) and dynamic moblity adaptive clustering algorithm (DMAC)

Abstract

This project addresses issues pertaining to mobile multi-hop radio networks called mobile ad hoc networks (MANET), which plays a critical role in places where a wired backbone is neither available nor economical to deploy. Our objective was to form and maintain clusters for efficient routing, scalability and energy utilization. To map the cellular architecture into the mobile ad hoc network cluster heads are elected that form the virtual backbone for packet transmission. However, the constant movement of the nodes changes the topology of the network, which perturbs the transmission. This demands the cluster maintenance. Weighed Clustering Algorithm (WCA)[4] and Distributed and Mobility adaptive Clustering (DMAC) [1,2,3] are two better proven algorithms on which we have implemented different mobility models like Random Walk (RW), Random Way Point (RWP) and Random Direction (RD). In both the algorithms each node is assigned some weight .In WCA the weight is a function of parameters like Battery power, mobility, transmission range and degree of connectivity. DMAC is mobility adaptive, i.e. it takes the mobility of the nodes into consideration while forming the clusters. We have chosen some measuring parameters like no of clusterheads, Average cluster lifetime, and Reaffilation rate for comparing the performance of both the algorithms.