Heterogeneous node distribution clustering routing algorithm for wireless sensor network

2013 ◽  
Vol 33 (12) ◽  
pp. 3415-3418 ◽  
Author(s):  
Kaiguo QIAN ◽  
Zucheng DAI ◽  
Shikai SHEN
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Node Distribution ◽  
Heterogeneous Node

Small world routing algorithm of wireless sensor network

2010 ◽  
Vol 30 (9) ◽  
pp. 2497-2500
Author(s):  
Xiu-li REN ◽  
Jiang-ying DONG ◽  
Jian-sheng XUE
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Small World ◽  
Wireless Sensor

scholarly journals An Energy-efficient Mobile Routing Algorithm in Wireless Sensor Network

2015 ◽  
Vol 8 (4) ◽  
pp. 137-146
Author(s):  
Lin Zhigui ◽  
Li Min ◽  
Liu Yingping ◽  
Yang Ziyuan ◽  
Zhang Huiqi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Wireless Sensor

A Recursive Shortest Path Routing Algorithm With Application for Wireless Sensor Network Localization

2016 ◽  
Vol 16 (11) ◽  
pp. 4631-4637 ◽  
Author(s):  
Juan Cota-Ruiz ◽  
Pablo Rivas-Perea ◽  
Ernesto Sifuentes ◽  
Rafael Gonzalez-Landaeta
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Shortest Path ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Sensor Network Localization ◽  
Shortest Path Routing ◽  
Network Localization

scholarly journals Unequal Clustering Multipath Routing Algorithm for Wireless Sensor Network based on Clustering and Ant Colony

2021 ◽  
Vol 3 (3) ◽  
pp. 156-160
Author(s):  
Jin Yong-xian
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Multipath Routing ◽  
Cluster Head ◽  
Optimal Number ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Selection Probability ◽  
Factor Node

To improve the energy efficiency of the wireless sensor network (WSN), and extend the network life. This paper proposes an improved unequal clustering multipath routing algorithm (UCMRA). The algorithm improves the formula of cluster head selection probability and competition radius, and considers the energy factor, node density, optimal number of cluster heads, etc. Experimental results show that, compared with the traditional algorithm, UCMRA has more stable cluster head distribution, less energy consumption and longer network lifetime.

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