Energy balanced uneven clustering algorithm based on ant colony for wireless sensor network

2013 ◽  
Vol 33 (12) ◽  
pp. 3410-3414 ◽  
Author(s):  
Congcong MIAO ◽  
Qingkui CHEN ◽  
Jianwei CAO ◽  
Gang ZHANG
Author(s):  
Kaki Ramya Sree

Due to the hopeful application of gathering information from unreachable position, wireless sensor network creates an immense challenge for data routing to maximize the communication with more energy efficient. In order to design the energy efficient routing, the optimization based clustering protocols are more preferred in wireless sensor network. In this paper, we have proposed competent optimization based algorithm called ANT colony Optimization clustering algorithm for creating the energy efficient routing path. WSNs comprise of countless spatially dispersed sensor hubs associated through the remote medium to screen and record the actual data from the climate. The hubs of WSN are battery controlled, so after a specific period it free whole energy. This energy limitation influences the lifetime of the organization. The goal of this review is to limit the generally energy utilization and to boost the organization lifetime. In this paper, a new method to optimize number of clusters is presented with suitable results..


2013 ◽  
Vol 32 (4) ◽  
pp. 920-923
Author(s):  
Ding DING ◽  
Fang-ai LIU ◽  
Qian-qian LI ◽  
Guang-xu YANG

2016 ◽  
Vol 12 (10) ◽  
pp. 86 ◽  
Author(s):  
Jingyi Bo ◽  
Yubin Wang ◽  
Na Xu

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; -ms-layout-grid-mode: line; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Combining the characteristics of wireless sensor network, the ant colony algorithm is applied to a wireless sensor network, and a wireless sensor network route algorithm based on energy equilibrium is proposed in this paper. This algorithm takes the energy factor into the consideration of selection of route based on probability and enhanced calculation of information so as to find out the optimal route from the source node to the target node with low cost and balanced energy, and it prolongs the life cycle of the whole network</span><span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">.</span>


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