Residential College | false |
Status | 已發表Published |
Bio-inspired energy efficient clustering approach for wireless sensor networks | |
Israel Edem Agbehadji1; Richard C. Millham1; Simon James Fong2; Jason J. Jung3; Khac-Hoai Nam Bui4; Abdultaofeek Abayomi1; Samuel Ofori Frimpong1 | |
2019-12-26 | |
Conference Name | 2019 International Conference on Wireless Networks and Mobile Communications, WINCOM 2019 |
Source Publication | Proceedings - 2019 International Conference on Wireless Networks and Mobile Communications, WINCOM 2019 |
Pages | 8942532 |
Conference Date | 29 Oct.-1 Nov. 2019 |
Conference Place | Fez, Morocco |
Country | Morocco |
Publication Place | IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA |
Publisher | IEEE |
Abstract | In this paper, we proposed an approach to clustering based on bio-inspired behaviour and distributed energy efficient model. The motivation to propose this clustering approach is due to the challenge of performance in terms of finding an efficient way to send data packets to base stations and to maintain the lifetime performance of wireless sensor networks. The bio-inspired approach adopted the behaviour of a bird called Kestrel. This behaviour is expressed using mathematical formulation and then translated into an algorithm. The bio-inspired algorithm is combined with the distributed energy efficient model for clustering to ensure efficient energy optimization. The proposed clustering approach, referred to as DEEC-KSA, is evaluated through simulation and compared with benchmarked clustering algorithms. The result of simulation showed that the performance of DEEC-KSA is efficient among the comparative clustering algorithms for energy optimization in terms of stability period, network lifetime and network throughput. Additionally, the proposed DEEC-KSA has the optimal time (in seconds) to send packets to base station successfully. |
Keyword | Edge Computing Load Balancing Wireless Sensor Network Clustering Algorithm Kestrel-based Search Algorithm Heterogeneous Environment Internet Of Things (Iot) Analytics |
DOI | 10.1109/WINCOM47513.2019.8942532 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science ; Engineering ; Telecommunications |
WOS Subject | Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications |
WOS ID | WOS:000560361900020 |
Scopus ID | 2-s2.0-85078160774 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Corresponding Author | Israel Edem Agbehadji |
Affiliation | 1.ICT and Society Research Group, Department of Information Technology, Durban University of Technology Durban, South Africa 2.ICT and Society Research Group, Department of Computer and Information Science, University of Macau Taipa, Macau SAR 3.Chung-Ang University Seoul, South Korea 4.Korea Institute of Science and Technology Information Daejeon, South Korea. |
Recommended Citation GB/T 7714 | Israel Edem Agbehadji,Richard C. Millham,Simon James Fong,et al. Bio-inspired energy efficient clustering approach for wireless sensor networks[C], IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2019, 8942532. |
APA | Israel Edem Agbehadji., Richard C. Millham., Simon James Fong., Jason J. Jung., Khac-Hoai Nam Bui., Abdultaofeek Abayomi., & Samuel Ofori Frimpong (2019). Bio-inspired energy efficient clustering approach for wireless sensor networks. Proceedings - 2019 International Conference on Wireless Networks and Mobile Communications, WINCOM 2019, 8942532. |
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