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Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications

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Abstract

Energy is vital parameter for communication in Internet of Things (IoT) applications via Wireless Sensor Networks (WSN). Genetic algorithms with dynamic clustering approach are supposed to be very effective technique in conserving energy during the process of network planning and designing for IoT. Dynamic clustering recognizes the cluster head (CH) with higher energy for the data transmission in the network. In this paper, various applications, like smart transportation, smart grid, and smart cities, are discussed to establish that implementation of dynamic clustering computing-based IoT can support real-world applications in an efficient way. In the proposed approach, the dynamic clustering-based methodology and frame relay nodes (RN) are improved to elect the most preferred sensor node (SN) amidst the nodes in cluster. For this purpose, a Genetic Analysis approach is used. The simulations demonstrate that the proposed technique overcomes the dynamic clustering relay node (DCRN) clustering algorithm in terms of slot utilization, throughput and standard deviation in data transmission.

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Authors and Affiliations

  1. Department of CSE, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, 140401, India

    Shalli Rani

  2. Department of CS, Georgia Southern University, Statesboro, GA, 30460, USA

    Syed Hassan Ahmed

  3. Department of Computing and Information Technology, University of Bisha, Bisha, Saudi Arabia

    Ravi Rastogi

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  1. Shalli Rani
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  2. Syed Hassan Ahmed
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  3. Ravi Rastogi
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Correspondence to Shalli Rani.

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Rani, S., Ahmed, S.H. & Rastogi, R. Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications. Wireless Netw 26, 2307–2316 (2020). https://doi.org/10.1007/s11276-019-02083-7

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