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TitleAn Energy-Efficient Cross-Layer-Sensing Clustering Method Based on Intelligent Fog Computing in WSNs
Creator
Date Issued2019
Source PublicationIEEE Access
ISSN2169-3536
Volume7Pages:144165-144177
Abstract

The conventional data-based routing protocols are usually vulnerable to a large number of energy voids or hotspots in Wireless Sensor Networks (WSNs). In order to address this problem, we propose Mobile Intelligent Fog Computing: An Energy-efficient Cross-layer-sensing Clustering Method (ECCM). The first, according to the cross-layer projection principle, the proposed algorithm employs the sensing-event-driven mechanism to project the fog nodes onto the sensing layer, and constructs a powerful virtual control node. Then the control procedure of the cluster-based routing protocol in sensor networks is uploaded to the fog layer and the fog computation is employed to achieve the distributed clustering of the event-field nodes. The second, the optimized data aggregation routing is constructed, which centers the projectile fog nodes. The data in the bottom-layer routing of the sensor network is thus replaced, and the network load is balanced and reduced. The third, in the optimization of the routing protocol, we introduce the Particles Swarm Optimization, (PSO) algorithm and elect a group of optimal nodes as the cluster heads, without the cost of any competition overhead, the energy overhead of the network can be effectively reduced and balanced, which curbs the rapid exhaustion of the node energy and prolongs the network lifetime. Finally, it is shown by the simulation results that the construction and the maintenance of the routing structure are small, which could optimize the data aggregation efficiency and improve the network performance.

Keywordclustering method Fog computation particles swarm optimization routing protocol wireless sensor network
DOI10.1109/ACCESS.2019.2944858
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000498836200008
Scopus ID2-s2.0-85073601468
Citation statistics
Cited Times:33[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/7142
CollectionResearch outside affiliated institution
Corresponding AuthorXu, Chen
Affiliation
1.School of Computer Science and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, 471023, China
2.Key Laboratory of Intelligent IoT, Luoyang Institute of Science and Technology, Luoyang, 471023, China
3.School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, 200235, China
4.College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China
5.School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, 510006, China
6.Department of Computer Science and Engineering, Zhejiang Normal University, Jinhua, 321004, China
Recommended Citation
GB/T 7714
Sun, Zeyu,Wei, Lili,Xu, Chenet al. An Energy-Efficient Cross-Layer-Sensing Clustering Method Based on Intelligent Fog Computing in WSNs[J]. IEEE Access, 2019, 7: 144165-144177.
APA Sun, Zeyu., Wei, Lili., Xu, Chen., Wang, Tian., Nie, Yalin., .. & Lu, Jianfeng. (2019). An Energy-Efficient Cross-Layer-Sensing Clustering Method Based on Intelligent Fog Computing in WSNs. IEEE Access, 7, 144165-144177.
MLA Sun, Zeyu,et al."An Energy-Efficient Cross-Layer-Sensing Clustering Method Based on Intelligent Fog Computing in WSNs". IEEE Access 7(2019): 144165-144177.
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