Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks
Journal article
Liu, Xiaozhu, Zhu, Rongbo, Anjum, Ashiq, Wang, Jun, Zhang, Hao and Ma, Maode 2019. Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks. Future Generation Computer Systems. 104, pp. 1-14. https://doi.org/10.1016/j.future.2019.10.001
| Authors | Liu, Xiaozhu, Zhu, Rongbo, Anjum, Ashiq, Wang, Jun, Zhang, Hao and Ma, Maode |
|---|---|
| Abstract | Data fusion can effectively reduce the amount of data transmission and network energy consumption in wireless sensor networks (WSNs). However the existing data fusion schemes lead to additional delay overhead and power consumptions. In order to improve the performance of WSNs, an intelligent data fusion algorithm based on hybrid delay-aware clustering (HDC) in WSNs is proposed, which combines the advantages of single-layer cluster structure and multi-layer cluster structure, and adaptive selects the clustering patterns of the cluster by the decision function to achieve the tradeoff between network delay and energy consumption. The network model of HDC is presented, and theoretical analysis of the delay and energy consumption of single-layer cluster and multi-layer cluster are provided. And the energy efficient clustering algorithm and the dynamic cluster head re-selection algorithm are proposed to optimize network energy consumption and load balancing of the network. Simulation results show that, compared with the existing delay-aware models, the proposed scheme can effectively reduce the network delay, network energy consumption, and extend the network lifetime simultaneously. |
| Keywords | Computer Networks and Communications; Hardware and Architecture; Software |
| Year | 2019 |
| Journal | Future Generation Computer Systems |
| Journal citation | 104, pp. 1-14 |
| Publisher | Elsevier |
| ISSN | 0167-739X |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.future.2019.10.001 |
| Web address (URL) | http://hdl.handle.net/10545/624464 |
| http://creativecommons.org/publicdomain/zero/1.0/ | |
| hdl:10545/624464 | |
| Publication dates | 04 Oct 2019 |
| Publication process dates | |
| Deposited | 06 Feb 2020, 16:24 |
| Accepted | 01 Oct 2019 |
| Rights | CC0 1.0 Universal |
| Contributors | Wuhan University of Technology, Wuhan, China, South-Central University for Nationalities, Wuhan, China, University of Derby and Nanyang Technological University, Singapore |
| File | File Access Level Open |
| File | File Access Level Open |
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