SCAM: Scenario-based Clustering Algorithm for Mobile ad hoc networks

This paper proposes a scenario based, adaptive and distributed clustering algorithm SCAM (Scenario-based Clustering Algorithm for Mobile ad hoc networks). A distributed algorithm based on (k, r) - Dominating Set is used for the selection of clusterheads and gateway nodes, here k is the minimum number of clusterheads per node in the network and r is the maximum number of hops between the node and the clusterhead. From among the k dominating nodes, the non-clusterhead node can select the most qualified dominating node as its clusterhead. The quality of the clusterhead is calculated based on various metrics, which include connectivity, stability and residual battery power. Long-term service as clusterhead depletes their energy, causing them to drop out of the network. Similarly, the clusterhead with relatively high mobility than its neighbours leads to frequent clusterhead election process. This perturbs the stability of the network and adversely affects the performance of the network. Load balancing among clusterheads and correct positioning of clusterhead in a cluster are also vital to increase the life span of the network. The proposed algorithm periodically calculates the quality of all dominating nodes and if it goes below the threshold level it resigns the job as clusterhead and sends this message to all other member nodes. Since these nodes have k dominating nodes within r - hop distance, it can choose the current best-qualified node as its clusterhead. SCAM uses techniques to maintain the cluster structure as stable as possible with less control messages.