Status | 已发表Published |
Title | An Energy-Efficient Cross-Layer-Sensing Clustering Method Based on Intelligent Fog Computing in WSNs |
Creator | |
Date Issued | 2019 |
Source Publication | IEEE Access
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ISSN | 2169-3536 |
Volume | 7Pages: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. |
Keyword | clustering method Fog computation particles swarm optimization routing protocol wireless sensor network |
DOI | 10.1109/ACCESS.2019.2944858 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Computer Science ; Engineering ; Telecommunications |
WOS Subject | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
WOS ID | WOS:000498836200008 |
Scopus ID | 2-s2.0-85073601468 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/7142 |
Collection | Research outside affiliated institution |
Corresponding Author | Xu, 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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