casa 20(20): e1

Research Article

Energy Efficiency to Improve Network Life Time Using Particle Swarm Optimization Algorithm

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  • @ARTICLE{10.4108/eai.13-7-2018.163974,
        author={S. Kannadhasan and S. Deepa and M. Shanmuganantham},
        title={Energy Efficiency to Improve Network Life Time Using Particle Swarm Optimization Algorithm},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={7},
        number={20},
        publisher={EAI},
        journal_a={CASA},
        year={2020},
        month={4},
        keywords={WSN, PSO, Throughput, Analysis of Node and Energy Efficiency},
        doi={10.4108/eai.13-7-2018.163974}
    }
    
  • S. Kannadhasan
    S. Deepa
    M. Shanmuganantham
    Year: 2020
    Energy Efficiency to Improve Network Life Time Using Particle Swarm Optimization Algorithm
    CASA
    EAI
    DOI: 10.4108/eai.13-7-2018.163974
S. Kannadhasan1,*, S. Deepa2, M. Shanmuganantham3
  • 1: Cheran College of Engineering, Department of Electronics and Communication Engineering, Karur, Tamilnadu, India
  • 2: Madurai Kamaraj University Evening College, Department of Computer Science, Madurai, Tamilnadu, India
  • 3: Tamilnadu Government Polytechnic College, Department of Electrical and Electronics Engineering, Madurai, Taminadu, India
*Contact email: kannadhasan.ece@gmail.com

Abstract

Remote Sensor Networks (WSNs) have a developing innovation for different applications in reconnaissance, condition, natural surroundings observing, medicinal services and fiasco administration. It has monitor through environment by using sensing device that means of physical properties. WSN is a network that can transmit and receive through the wireless medium by using the sensor devices for various nodes. There are various base stations to control final destination of data from one place to other place. It includes the dense ad-hoc deployment, dynamic topology, spatial distribution, and Network topology, Graph Theory with constraint the bandwidth, energy life time and memory. Based on the problem size increases, it can require as various efforts by using the optimization techniques. This paper is to distinguish the deficiencies in Wireless Sensor Networks the hubs have transmitted starting with one place then onto the next by utilizing the particle swarm enhancement. PSO calculation is contrasted and the different calculations PCA, Neural system and OPAST. Based on the algorithm, the performance analysis is done on specificity, fault detection and fault coverage. The simulation result shows the energy life time, throughput, packet delivery ratio produces good performance when compared to the other algorithms.