ISSN 2996-8223
International Journal of Computer Science and Technology | Vol. 9, No. 3, March 2007 | pp. 25–32
DOI: 10.46882/2007/IJCST/930025
Article Type: Original Research Article
Title: An Optimized Energy-Efficient Routing Protocol for Mobile Ad-Hoc Networks Based on Genetic Algorithms
Names of Authors: James C. Nwosu¹, Elena R. Rostov²
Authors’ Affiliations: ¹Department of Computer Science, Faculty of Science, University of Nigeria, Nsukka, Nigeria; ²School of Computing and Information Systems, University of Melbourne, Victoria, Australia
Abstract: Mobile Ad-hoc Networks (MANETs) are characterized by dynamic topologies and constrained energy resources, which make network longevity a critical design challenge. Traditional routing protocols frequently fail to optimize energy consumption evenly across nodes, leading to premature network partitioning. This paper presents an Optimized Energy-Efficient Routing Protocol (OEERP) that utilizes genetic algorithms to identify optimal paths based on residual energy and hop count metrics. The primary objective is to maximize network lifetime while maintaining a stable Quality of Service (QoS). Simulation models were executed under varying node density conditions (n = 50, 100, and 150 nodes) across a 1000 m x 1000 m simulation area. Statistical evaluations indicate that OEERP reduces average energy consumption per packet by 18.4% ± 1.2% compared to standard Ad-hoc On-Demand Distance Vector (AODV) routing. Furthermore, the packet delivery ratio (PDR) improved by 6.5%, maintaining an average PDR of 94.2% under high mobility speeds of 20 m/s. The mathematical objective function combines residual node energy (E_res) and path propagation delay (D_packet) using scaled weights (w₁ = 0.6, w₂ = 0.4) to systematically discard weak pathways. These results demonstrate that evolutionary computational strategies can successfully stabilize unstable network topologies.
Keywords: Mobile Ad-hoc Networks; Energy Efficiency; Genetic Algorithms; Routing Protocols; Network Longevity; AODV Optimizations
Manuscript Timeline: Received: November 12, 2006; Revised: January 15, 2007; Accepted: February 18, 2007; Published: March 28, 2007.
Citation: International Journal of Computer Science and Technology, Vol. 9, No. 3, March 2007, pp. 25–32, DOI: 10.46882/2007/IJCST/930025.
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