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Energy efficient and delay aware clustering in mobile adhoc network: A hybrid fruit fly optimization algorithm and whale optimization algorithm approach

S. Karunakaran, Thangavel Renukadevi

2022Concurrency and Computation Practice and Experience19 citationsDOI

Abstract

Abstract The energy efficient and delay are the two important optimization issues in the mobile adhoc network (MANET), where the nodes move randomly at any direction with limited battery life, resulting in occasional change of network topology. In this article, a hybrid fruit fly optimization algorithm and whale optimization algorithm (FOA‐WOA) is proposed for energy efficient with delay aware cluster head (CH) selection. The major objective of the proposed method is “to solve the problems of energy efficient with delay and develop a clustering mechanism”. The performance of the hybrid FOA‐WOA is evaluated based on packet delivery ratio (PDR), delay, energy consumption, and throughput. Moreover, the proposed method is analyzed with two existing algorithms, like ant colony optimization (ACO) and genetic algorithm (GA). The experimental results show that the proposed method attains 11.6% better than ACO and 1.8% better than GA based on packet delivery ratio, 57.6% better than ACO and 27.3% better than GA based on delay and 15.3% better than ACO and 36.4% better than GA based on energy consumption.

Topics & Concepts

Computer scienceAnt colony optimization algorithmsNetwork packetAlgorithmCluster analysisEnergy consumptionEnd-to-end delayGenetic algorithmThroughputEnergy (signal processing)Optimization algorithmMathematical optimizationComputer networkWirelessMathematicsArtificial intelligenceEngineeringMachine learningElectrical engineeringStatisticsTelecommunicationsMobile Ad Hoc NetworksCooperative Communication and Network CodingEnergy Efficient Wireless Sensor Networks
Energy efficient and delay aware clustering in mobile adhoc network: A hybrid fruit fly optimization algorithm and whale optimization algorithm approach | Litcius