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Antipredator Adaptation Shuffled Frog Leap Algorithm to Improve Network Life Time in Wireless Sensor Network

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Abstract

A Wireless Sensor Network (WSN) is an interdisciplinary discipline of sensing, electronics and wireless communication employed widely in environmental monitoring and surveillance applications. The sensor nodes are generally tiny and made of irreplaceable power source and limited capacity for computing, communication, and storage. The power constraint necessitates that the WSN routing protocols conserve energy as critical factor to maximize the network lifetime. Cluster-based approaches are popularly used for its energy efficiency where some nodes designated as Cluster Heads (CHs) organize WSNs for data aggregation and energy saving. The CH is responsible for gathering data from the cluster nodes and conveying it to the base station due to which higher energy drain occurs at CH leading to uneven network degradation. Thus, the selection of CH is critical for improving the WSN performance and lifetime. In this paper, a hybrid Shuffled Frog Leaping Algorithm (AASFLA) with antipredator capabilities to avoid the local minima is proposed. Results show avoidance of suboptimal solution compared to SFLA and particle swarm optimization.

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Authors and Affiliations

  1. Department of Information Technology, Kongu Engineering College, Erode, India

    S. Anandamurugan & T. Abirami

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  1. S. Anandamurugan
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  2. T. Abirami
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Correspondence to T. Abirami.

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Anandamurugan, S., Abirami, T. Antipredator Adaptation Shuffled Frog Leap Algorithm to Improve Network Life Time in Wireless Sensor Network. Wireless Pers Commun 94, 2031–2042 (2017). https://doi.org/10.1007/s11277-016-3354-1

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  • DOI: https://doi.org/10.1007/s11277-016-3354-1

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