Multi-Objective Cluster Head-Based Energy-Aware Routing Protocol using Hybrid Woodpecker and Flamingo Search Optimization Algorithm for Internet of Things Environment

P. Arivubrakan () and G. R. Kanagachidambaresan
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P. Arivubrakan: Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Avadi, Chennai, Tamil Nadu, India
G. R. Kanagachidambaresan: Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Avadi, Chennai, Tamil Nadu, India

International Journal of Information Technology & Decision Making (IJITDM), 2024, vol. 23, issue 02, 763-782

Abstract: Internet of Things (IoT) plays a vital role in the world of Internet and integrates computing devices. The digital machines provide unique identifiers. The capacity to send data through the network using a better path is one of the capabilities of digital machines. IoT generates huge data based on fast aggregation data and processes these data efficiently. In this paper, a multi-objective hybrid woodpecker and flamingo search optimization algorithm is proposed for finding optimum Cluster Head (CH)-based energy-aware routing protocol in IoTs environment (Hyb-WFSOA-CHS-IoT). Here, the proposed Hyb-WFSOA-CHS-IoT model executes routing method through CH. The woodpecker and flamingo search optimization algorithm is used as the intelligent CH selection that consumes same energy as sensors. Hybrid woodpecker and flamingo search optimization algorithm (Hyb-WFSOA) is examined by using fitness functions, like distance, delay, energy consumption, throughput. The proposed Hyb-WFSOA-CHS-IoT method is activated in MATLAB software. Then, the performance of the proposed system is examined with different metrics, like delay, packet delivery ratio, throughput, network lifetime, energy consumption. Therefore, the proposed method attains lower delay 28.38%, 32.34% and 47.45%, higher delivery ratio 19.34%, 23.12% and 18.96% and lower energy consumption 11.25%, 7.90% and 12.88% compared with existing methods, like multi-objective fractional gravitational search algorithm for energy-efficient routing on IoT (FGSA-CHS-IoT), multi-objective sunflower-based gray wolf optimization algorithm for multiple path routing on IoT network (SFG-CHS-IoT) and energy-aware routing in the IoT with improved grasshopper metaheuristic algorithm with chaos theory and fuzzy Logic (FLGOA-CHS-IoT).

Keywords: Cluster head selection; energy-aware routing protocol; Internet of Things; multipath routing; woodpecker and flamingo search optimization algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219622023500220

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