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ELR-C: A Multi-objective Optimization for Joint Energy and Lifetime Aware Cluster Based Routing for WSN Assisted IoT

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Abstract

The Wireless Sensor Network (WSN) serves as a medium for connecting the Internet of Things (IoT) physics and information network. Energy and lifetime are two important factors that contribute to a reliable network connection. WSN-IoT sensors have lower battery life due to network performance issues. However, the communication cost of the WSN-IoT network is very huge due to the power of the sensor network. Thus, WSN-IoT's difficulties are energy efficiency and network life. In this study, we investigate the multi-objective optimization for joint energy and lifetime aware cluster (ELR-C) based routing for WSN-IoT. The proposed ELR-C routing technique aimed to provide optimal clustering using multi-objective chaotic slime mold (MCSM) algorithm which ensures energy efficiency in overall WSN-IoT performance. Then, we utilize the multiple design metrics based on trust degree to calculate cluster head (CH) across several nodes. Then, the multiple design metrics are optimized through an improved Butterfly Optimization (IBO) algorithm. Finally, we illustrate cat hunting with a feed-forward neural network (CH-FFNN) for multi-hop routing between CHs and sink nodes to optimize both energy efficiency and network lifetime. Based on the simulation findings, the proposed ELR-C routing technique outperformed existing routing techniques in terms of energy and network lifetime.

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  1. Department of Electronics and Communication Engineering, SHUATS, Prayagraj, India

    Abhishek Srivastava & Rajeev Paulus

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  1. Abhishek Srivastava
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  2. Rajeev Paulus
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Correspondence to Abhishek Srivastava.

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Srivastava, A., Paulus, R. ELR-C: A Multi-objective Optimization for Joint Energy and Lifetime Aware Cluster Based Routing for WSN Assisted IoT. Wireless Pers Commun 132, 979–1006 (2023). https://doi.org/10.1007/s11277-023-10645-4

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