OCSO-CA: opposition based competitive swarm optimizer in energy efficient IoT clustering

doi:10.1007/s11704-021-0163-9

Front. Comput. Sci.

2022, Vol. 16

Issue (1) : 161501 https://doi.org/10.1007/s11704-021-0163-9

RESEARCH ARTICLE

OCSO-CA: opposition based competitive swarm optimizer in energy efficient IoT clustering

Arpita BISWAS¹, Abhishek MAJUMDAR²(

), Soumyabrata DAS³, Krishna Lal BAISHNAB¹

¹. Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, India
². Department of Computer Science & Engineering, Karunya Institute of Technology & Sciences, Coimbatore 641114, India
³. Department of Electrical Engineering, National Institute of Technology Silchar, Silchar 788010, India

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Abstract

With the advent of modern technologies, IoT has become an alluring field of research. Since IoT connects everything to the network and transmits big data frequently, it can face issues regarding a large amount of energy loss. In this respect, this paper mainly focuses on reducing the energy loss problem and designing an energy-efficient data transfer scenario between IoT devices and clouds. Consequently, a layered architectural framework for IoT-cloud transmission has been proposed that endorses the improvement in energy efficiency, network lifetime and latency. Furthermore, an Opposition based Competitive Swarm Optimizer oriented clustering approach named OCSO-CA has been proposed to get the optimal set of clusters in the IoT device network. The proposed strategy will help in managing intra-cluster and intercluster data communications in an energy-efficient way. Also, a comparative analysis of the proposed approach with the stateof-the-art optimization algorithms for clustering has been performed.

Keywords competitive swarm optimization cloud computing clustering IoT

Corresponding Author(s): Abhishek MAJUMDAR

Just Accepted Date: 14 April 2021 Issue Date: 28 September 2021

Cite this article:

Arpita BISWAS,Abhishek MAJUMDAR,Soumyabrata DAS, et al. OCSO-CA: opposition based competitive swarm optimizer in energy efficient IoT clustering[J]. Front. Comput. Sci., 2022, 16(1): 161501.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-021-0163-9
https://academic.hep.com.cn/fcs/EN/Y2022/V16/I1/161501

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