%A Arpita BISWAS, Abhishek MAJUMDAR, Soumyabrata DAS, Krishna Lal BAISHNAB %T OCSO-CA: opposition based competitive swarm optimizer in energy efficient IoT clustering %0 Journal Article %D 2022 %J Front. Comput. Sci. %J Frontiers of Computer Science %@ 2095-2228 %R 10.1007/s11704-021-0163-9 %P 161501-${article.jieShuYe} %V 16 %N 1 %U {https://journal.hep.com.cn/fcs/EN/10.1007/s11704-021-0163-9 %8 2022-02-15 %X

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.