Ant Colony Optimization and Genetic Algorithm Integrated Load Balancing Approach for MANET
K. B. Gurumoorthy1, S. Gopinath2, K. Vinoth Kumar3
1K. B.Gurumoorthy, Assistant Professor, Department of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore (Tamil Nadu), India.
2Dr. S.Gopinath, Associate Professor, Department of Information Technology, Karpagam Institute of Technology, Coimbatore (Tamil Nadu), India.
3Dr. K.Vinoth Kumar, Associate Professor, Department of Electronics and Communication Engineering, Karpagam Institute of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 399-405 | Volume-8 Issue-5, March 2019 | Retrieval Number: D2755028419/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Multi-path routing in Mobile Ad Hoc Networks (MANETs) minimizes latency and ensures on-demand back-up routing to prevail over route errors. Unplanned network load degrades individual node performance, preventing instant path switch-over. This increases overloading of the nodes and henceforth resulting in drops. We propose a two-phase optimization algorithm in a hybrid manner assimilating Ant Colony Optimization (ACO) and Genetic Approach (GA) to improve load handling capacity of the nodes with improved packet delivery at the destination. Both node and path selection are favored by conditional optimization in both the phases; concentrating in minimum switch-over and higher delivery rate. Precise path and neighbor selection by improved load handling capability minimizes packet drop and control overhead.
Keyword: Optimal Cluster Head Selection, Ant Colony Optimization, Genetic Algorithms, Load Balancing.
Scope of the Article: Cross Layer Design and Optimization