A Hybrid Delay Aware Clustered Routing Approach Using Aquila Optimizer and Firefly Algorithm in Internet of Things

Mehdi Hosseinzadeh, Liliana Ionescu-Feleaga, Bogdan-Ștefan Ionescu, Mahyar Sadrishojaei, Faeze Kazemian, Amir Masoud Rahmani () and Faheem Khan ()
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Mehdi Hosseinzadeh: Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
Liliana Ionescu-Feleaga: Department of Accounting and Audit, Bucharest University of Economic Studies, 010374 Bucharest, Romania
Bogdan-Ștefan Ionescu: Department of Management Information System, Bucharest University of Economic Studies, 010374 Bucharest, Romania
Mahyar Sadrishojaei: Faculty of Industry, University of Applied Science and Technology (UAST), Tehran 11369, Iran
Faeze Kazemian: Department of Computer Science, University of Applied Science and Technology (UAST), Tehran 11369, Iran
Amir Masoud Rahmani: Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
Faheem Khan: Department of Computer Engineering, Gachon University, Seongnam 13120, Republic of Korea

Mathematics, 2022, vol. 10, issue 22, 1-15

Abstract: Protocols for clustering and routing in the Internet of Things ecosystem should consider minimizing power consumption. Existing approaches to cluster-based routing issues in the Internet of Things environment often face the challenge of uneven power consumption. This study created a clustering method utilising swarm intelligence to obtain a more even distribution of cluster heads. In this work, a firefly optimization method and an aquila optimizer algorithm are devised to select the intermediate and cluster head nodes required for routing in accordance with the NP-Hard nature of clustered routing. The effectiveness of this hybrid clustering and routing approach has been evaluated concerning the following metrics: remaining energy, mean distances, number of hops, and node balance. For assessing Internet of things platforms, metrics like network throughput and the number of the living node are crucial, as these systems rely on battery-operated equipment to regularly capture environment data and transmit specimens to a base station. Proving effective, the suggested technique has been found to improve system energy usage by at least 18% and increase the packet delivery ratio by at least 25%.

Keywords: internet of things; clustered routing; aquila optimizer; firefly algorithm; energy efficient; lifespan (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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