Advances of Science and Technology. 6th EAI International Conference, ICAST 2018, Bahir Dar, Ethiopia, October 5-7, 2018, Proceedings

Research Article

Evolutionary Based Clustering Protocol for Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-030-15357-1_30,
        author={Melaku Tamene and Kuda Nageswara and Ravuri Daniel},
        title={Evolutionary Based Clustering Protocol for Wireless Sensor Networks},
        proceedings={Advances of Science and Technology. 6th EAI International Conference, ICAST 2018, Bahir Dar, Ethiopia, October 5-7, 2018, Proceedings},
        proceedings_a={ICAST},
        year={2019},
        month={3},
        keywords={Clustering protocol Wireless sensor networks Routing protocol},
        doi={10.1007/978-3-030-15357-1_30}
    }
    
  • Melaku Tamene
    Kuda Nageswara
    Ravuri Daniel
    Year: 2019
    Evolutionary Based Clustering Protocol for Wireless Sensor Networks
    ICAST
    Springer
    DOI: 10.1007/978-3-030-15357-1_30
Melaku Tamene1,*, Kuda Nageswara2,*, Ravuri Daniel3,*
  • 1: Wollo University
  • 2: Andhra University
  • 3: Debre Tabor University
*Contact email: melakutam2013@gmail.com, knraoauce@gmail.com, danielravuri@gmail.com

Abstract

Many cluster based routing protocols have been developed in order to enhance the network lifetime, but the potency of clustering in energy management highly relies on the optimality of clusters. Optimal cluster formation is the chief source of challenges in clustering protocols. In this paper, new approach has been introduced to formulate the optimization problem in the partition of networks into optimal organization of clusters. The optimization problem consists of finding optimal configuration of clusters such that the distance of cluster heads from the pre-computed cluster centers, communication cost of nodes to transport data and the expected energy dissipation of the network per the residual energy of cluster heads are minimized. The solution to the devised nonlinear clustering problem is found using the genetic algorithm. The genetic algorithm toolbox is developed in C++ and integrated with OMNeT++ simulation platform to implement the protocol. The experimental results verify that the proposed protocol extends the network lifetime compared to the prominent LEACH, LEACH-C and CHEF protocols.