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EEDCHS-PSO: Energy-Efficient Dynamic Cluster Head Selection with Differential Evolution and Particle Swarm Optimization for Wireless Sensor Networks (WSNS)

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Evolution in Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1176))

Abstract

The communication subsystem in WSNs is primarily responsible for energy consumption which becomes a consistent in the networks owing to the usage of non-rechargeable battery having a limited power supply. The technology of communicating through wireless mode is recommended in number of sensing applications as it is convenient to use affordable and reliable. Modern sensors are designed with compatibility to sense the factors of the environment and transfer them in wireless mode. The center which collects the information favor confined data that are being clustered from a set of sensors than gathering the data from individual sensors. In general, wireless sensor network (WSN) uses grouping algorithm for domestic and use in abroad for dynamic cluster head selection is considered to be a significant task. To resolve the issue of cluster head selection with greater coverage and balanced energy consumption during the formation of cluster, it is taken as an important aspect. In this formulated work, an efficient clustering algorithm is proposed for monitoring the environment called energy-efficient dynamic cluster head selection with particle swarm optimization (EEDCHS-PSO). The selection process of cluster heads (CHs) is carried depending on the calculation of ordinary transmission distance and lingering energy. It can be seen that the sensor nodes known as cluster head (CH) that performs the task to route the data from the cluster to the cluster head of other clusters or base stations. Proposed EEDCHS-DEBO shows better performance in energy competence, load balancing, and range of scale with low control overhead.

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Author information

Authors and Affiliations

  1. Sri Ramakrishna Engineering College, Coimbatore, India

    T. Guhan

  2. Hindusthan College of Arts and Science, Coimbatore, India

    N. Revathy & B. Sathyabama

  3. Karpagam College of Engineering, Coimbatore, India

    K. Anuradha

Authors
  1. T. Guhan
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  2. N. Revathy
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  3. K. Anuradha
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  4. B. Sathyabama
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Corresponding author

Correspondence to T. Guhan .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Sheng-Lung Peng

  3. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  4. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

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Guhan, T., Revathy, N., Anuradha, K., Sathyabama, B. (2021). EEDCHS-PSO: Energy-Efficient Dynamic Cluster Head Selection with Differential Evolution and Particle Swarm Optimization for Wireless Sensor Networks (WSNS). In: Bhateja, V., Peng, SL., Satapathy, S.C., Zhang, YD. (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore. https://doi.org/10.1007/978-981-15-5788-0_67

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