基于非均匀分簇和信息熵的无线传感网络路由算法

Liu, Jia, Fan, Shurui, Liu, Yanping, Liu, Jianlong, Peng, Mingsha and Guo, Haihong (2015) 基于非均匀分簇和信息熵的无线传感网络路由算法. 传感技术学报, 28 12: 1867-1872. doi:10.3969/j.issn.1004-1699.2015.12.023


Author Liu, Jia
Fan, Shurui
Liu, Yanping
Liu, Jianlong
Peng, Mingsha
Guo, Haihong
Title 基于非均匀分簇和信息熵的无线传感网络路由算法
Translated title A routing algorithm for WSNs based on uneven clustering and entropy theory
Language of Title chi
Journal name 传感技术学报
Translated journal name Chinese Journal of Sensors and Actuators
Language of Journal Name chi
ISSN 1004-1699
Publication date 2015-12-01
Sub-type Article (original research)
DOI 10.3969/j.issn.1004-1699.2015.12.023
Open Access Status Not Open Access
Volume 28
Issue 12
Start page 1867
End page 1872
Total pages 6
Place of publication Nanjing, Jiangsu, China
Publisher Dongnan Daxue / Southeast University
Language chi
Abstract An energy efficient routing algorithm is the major concern in wireless sensor networks(WSNs),especial?ly the hot spot,because of unbalanced energy consumption. Based on uneven clustering and entropy theory,a kind of improved routing algorithm is proposed for solving that problem. In the process of cluster head election and com?petition radius calculation,node energy,density and distance to BS are considered to effectively balance energy con?sumption and prolong the life cycle of cluster head nodes. Meanwhile the hybrid rules of single-hop and multi-hop routing is adopted to reduce the energy consumption among clusters. Introducing fusion weight coefficient,informa?tion entropy mechanism is used for reducing the uncertainty and improving the efficiency of data fusion. Simulation results show that compared with LEACH,EEUC and EBUCA,the new algorithm can balance energy consumption and prolong the life cycle of wireless sensor networks.
Keyword Energy efficient
Entropy theory
Routing protocol
Uneven clustering
Wireless sensor network
Q-Index Code CX
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Non HERDC
 
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