SM-MEC: Spider Monkey Algorithm Based Mobility Aware Energy Efficient Clustering for MANET

Abstract

Background: In Mobile Ad-Hoc Network (MANET), clustering has been proved as an effective technique to increase overall network lifetime. However, cluster heads (CHs) and gateway nodes consume more energy due to their role of intra-cluster and inter-cluster transmission. Therefore, the judicious selection of CHs plays a preeminent concern in clustering for prolonging the network lifetime of such network where battery dependency and mobility are basic constraints.

Method: This paper includes a proposal for an energy-effective and mobility aware clustering algorithm for MANET using a Spider Monkey Optimization (SMO) algorithm. For energy efficiency and mobility awareness different parameters have been considered like node’s residual energy, distance with other nodes, mobility and the direction of mobility.

Result: The algorithm is tested extensively in different scenarios by changing a measure of nodes. The simulation outcomes are evaluated against the currently used similar algorithm to demonstrate the effectiveness of the suggested algorithm.

Conclusion: The algorithm proves to be more efficient in terms of cluster head selection.