Optimized AODV Routing Algorithm in MANET for Maximizing the Network Lifetime
B. Kameswara Rao1, A.S.N. Chakravarthy2
1B. Kameswara Rao, Department of Computer Science Engineering, Aditya Institute of Technology and Management, Affiliated to JNTUK University, Tekkali, India,
2Dr A.S.N. Chakravarthy, Professor, Department of Computer Science Engineering, JNTUKUCEV University, Vizianagaram, India.
Manuscript received on 04 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 4054-4059 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3457078219/19©BEIESP | DOI: 10.35940/ijrte.B3457.078219
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: In present scenario, Mobile Ad-hoc Networks (MANETs) is the emerging research topic in the applications like disaster situations (battle fields, earthquake, etc). The utility of MANET is increased by combining with the internet. The conventional techniques in MANET have a few issues like less infrastructure, standalone networks, and dynamic or complex topology. In order to address these issues, an efficient clustering and channeling algorithm (Hybrid K-means, Particle Swarm Optimization (PSO) based Ad-hoc On-demand Distance Vector (AODV) channeling algorithm) is developed for maximizing the network lifetime. The proposed algorithm finds the optimal cluster head selection for discovering the shortest path among the cluster heads. The Hybrid-K-means-PSO-AODV technique is applied to increase the Network Lifetime (NL), alive nodes, total packet send, throughput, and also to minimizes the dead nodes and energy consumption in a network. In the experimental phase, the proposed approach reduced the emery consumption up to 170 joules related to the existing approaches: PSO-PSO- MANETs and PSO-GSO- MANETs.
Keywords: Ad-hoc on-Demand Distance Vector, K-Means Clustering, Mobile Ad-Hoc Networks, Network Lifetime, and Particle Swarm Optimization.
Scope of the Article: Mobile Ad-hoc Network