Load Balanced Clustering Technique in MANET using Genetic Algorithms

M. Kaliappan; E. Mariappan; M. Viju Prakash; B. Paramasivan

doi:10.14429/dsj.66.9205

M. Kaliappan Department of Information Technology , National Engineering College, Kovilpatti
E. Mariappan Department of Information Technology, Jayaraj Annapackiam C.S.I. College of Engineering, Nazareth
M. Viju Prakash Department of Computer Science and Engineering, St. Xavier’s Catholic College of Engineering, Nagercoil
B. Paramasivan Department of Computer Science and Engineering, National Engineering College, Kovilpatti

DOI: https://doi.org/10.14429/dsj.66.9205

Keywords: Clustering, genetic algorithm, load-balancing, mobile adhoc networks

Abstract

Mobile adhoc network (MANET) has characteristics of topology dynamics due to factors such as energy conservation and node movement that leads to dynamic load-balanced clustering problem (DLBCP). Load-balancing and reliable data transfer between all the nodes are essential to prolong the lifetime of the network. MANET can also be partitioned into clusters for maintaining the network structure. Generally, Clustering is used to reduce the size of topology and to accumulate the topology information. It is necessary to have an effective clustering algorithm for adapting the topology change. In this, we used energy metric in genetic algorithm (GA) to solve the DLBCP. It is important to select the energy- efficient cluster head for maintaining the cluster structure and balance the load effectively. In this work, we used genetic algorithms such as elitism based immigrants genetic algorithm (EIGA) and memory enhanced genetic algorithm (MEGA) to solve DLBCP. These schemes select an optimal cluster head by considering the distance and energy parameters. We used EIGA to maintain the diversity level of the population and MEGA to store the old environments into the memory. It promises the load -balancing in cluster structure to increase the lifetime of the network. Experimental results show that the proposed schemes increases the network lifetime and reduces the total energy consumption. The simulation results show that MEGA and EIGA give a better performance in terms of load-balancing.

Author Biographies

M. Kaliappan, Department of Information Technology , National Engineering College, Kovilpatti

Dr M. Kaliappan received his PhD in Information and Communication Engineering from Anna University, Tamilnadu, India. Presently working as an Assistant Professor in the Department of Information Technology, National Engineering College, Kovilpatti, Tamilnadu, India. His research interests include : Wireless ad-hoc networks, and big data analytics.

E. Mariappan, Department of Information Technology, Jayaraj Annapackiam C.S.I. College of Engineering, Nazareth

Dr E. Mariappan received his PhD in Computer Science and Engineering from Manonmaniam Sundaranar University, Tamilnadu, India. Presently working as an Assistant Professor in the Department of Information Technology, National Engineering College, Kovilpatti, Tamilnadu, India. His research interests include : Wireless sensor and ad-hoc networks.

M. Viju Prakash, Department of Computer Science and Engineering, St. Xavier’s Catholic College of Engineering, Nagercoil

Mr M. Viju Prakash received his ME from Anna University, Chennai, Tamilnadu, India. Presently working as an Assistant Professor in the Department of Computer Science and Engineering, St. Xavier’s Catholic College of Engineering, Nagercoil, Tamil Nadu, India. His research interests include Wireless sensor networks.

B. Paramasivan, Department of Computer Science and Engineering, National Engineering College, Kovilpatti

Dr B.Paramasivan received his PhD degree in Information and Communication Engineering from Anna University, Tamilnadu, India. Presently working as a Professor in the Department of Computer Science and Engineering, St. Xavier’s Catholic College of Engineering, Nagercoil, Tamil Nadu, India. His research interests include wireless networking, and wireless sensor networks.