MHCF-CECSO: A Novel High-Performance Clustering Framework for Industrial IoT

doi:10.1109/JIOT.2023.3302236

CQUET-IR

	MHCF-CECSO: A Novel High-Performance Clustering Framework for Industrial IoT
	Gong, Yunping 1; Li, Chaoqun 2; Wang, Fengjiang 3; Fang, Xiaosheng 4
	2023
发表期刊	IEEE Internet of Things Journal
ISSN	2327-4662
EISSN	2327-4662
卷号	11 期号:3 页码:1-1
摘要	With the rapid development of the industrial Internet of things (IIoT), the industrial wireless sensor network (IWSN) with strong information perception capability and strict service quality requirements has been derived. The robust operation of the network plays a crucial role in the collection and transmission of important industrial information. Therefore, it is imperative to solve the problems of short network life and low quality of service (QoS). Considering these problems, this paper comprehensively considers the energy consumption, remaining energy, packet loss rate and delay, and designs a new multi-objective clustering model to accurately and reasonably elect cluster heads. Based on the advantages of the model, a novel multi-objective high-performance clustering framework (namely MHCF-CECSO) is proposed to improve the overall performance of IWSN. Specifically, in MHCF-CECSO, a novel chaotic multi-level elite clone snake optimization method is designed to enhance the optimal clustering mechanism. To further improve the clustering efficiency of MHCF-CECSO, chaos optimization is designed to perform an initial search for the snake group to enhance the diversity of the snake group and the algorithm's ability to escape from local optimum. In addition, a new multi-level elite cloning strategy is designed, which effectively improves the convergence speed of MHCF-CECSO. Comparing experiments with three state-of-the-art clustering schemes are conducted in four different scenarios, and the results show that the proposed MHCF-CECSO outperforms the other three comparison schemes in terms of network lifetime, energy consumption control and reliability. IEEE
关键词	Cloning Cluster analysis Clustering algorithms Energy utilization Internet of things Packet loss Wireless sensor networks Clusterings Delay Energy-consumption Industrial internet of thing Multi-level elite and clone strategy Multilevels Optimizers Packets loss Quality-of-service Snake optimizer Voting
DOI	10.1109/JIOT.2023.3302236
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001166992300089
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20233214504407
原始文献类型	Article in Press
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.cqcet.edu.cn/handle/39TD4454/17956
专题	重庆电子科技职业大学
作者单位	1.Chongqing College of Electronic Engineering, Chongqing, China; 2.College of Computer Science and Technology, Shandong University, Qingdao, China; 3.College of Information Science and Technology, Shihezi University, Shihezi, China; 4.Department of Electronic and Information Engineering, College of Engineering, Shantou University, Shantou, China
第一作者单位	重庆电子科技职业大学
推荐引用方式 GB/T 7714	Gong, Yunping,Li, Chaoqun,Wang, Fengjiang,et al. MHCF-CECSO: A Novel High-Performance Clustering Framework for Industrial IoT[J]. IEEE Internet of Things Journal,2023,11(3):1-1.
APA	Gong, Yunping,Li, Chaoqun,Wang, Fengjiang,&Fang, Xiaosheng.(2023).MHCF-CECSO: A Novel High-Performance Clustering Framework for Industrial IoT.IEEE Internet of Things Journal,11(3),1-1.
MLA	Gong, Yunping,et al."MHCF-CECSO: A Novel High-Performance Clustering Framework for Industrial IoT".IEEE Internet of Things Journal 11.3(2023):1-1.