Ant colony system based clustering routing algorithm for large-scale wireless sensor networks

Author(s):  
Liwan Chen ◽  
Mincan Xu ◽  
Qiang Chen ◽  
Yong Ran ◽  
Hongbing Li
2017 ◽  
Vol 13 (07) ◽  
pp. 4
Author(s):  
Xiaobin Shu ◽  
Caihong Liu ◽  
Chunxia Jiao ◽  
Qin Wang ◽  
Hongfeng Yin

<span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">To d</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">esign an effective secure routing of trusted nodes in wireless sensor networks</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">, </span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">quantum ant colony algorithm is applied to the design of large-scale wireless sensor network routing. The trustworthy network is used as the pheromone distribution strategy.</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">Then</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">,</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US"> the pheromone is encoded by the quantum bit</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">. The pheromone is updated by the quantum revolving door, and the energy consumption prediction is carried out to select the path. Finally, the trusted security routing algorithm of the wireless sensor network based on the global energy balance is realized. </span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">The quantum ant colony algorithm is superior to the traditional ant colony algorithm in algorithm convergence speed and global optimization. It can balance the energy consumption of the network node and can effectively resist the attacks such as Wormholes.</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">It is very promising to apply the quantum ant colony algorithm to the routing algorithm of large scale wireless sensor networks.</span>


2014 ◽  
Vol 945-949 ◽  
pp. 2394-2397
Author(s):  
Jun Ye Zhang ◽  
Dong Ya Chen

Due to the special demand of energy control and balancing the energy of nodes in wireless sensor networks,multipath routing based on ant colony system(MACS)was proposed. The algorithm utilizes the self-organization,self-adaptability and dynamic optimization capabilities of the ant colony to find the optimal routing and suboptimal routing from sources to Sink.Simulation results show the algorithm balances energy consumption of nodes and extends network lifetime effectively.


2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Sohail Jabbar ◽  
Rabia Iram ◽  
Muhammad Imran ◽  
Awais Ahmad ◽  
Anand Paul ◽  
...  

Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases, that is, route discovery, forwarding node, and route selection. We have improved the route discovery procedure and mainly concentrate on energy efficient forwarding node and route selection, so that the network lifetime can be prolonged. The four possible cases of forwarding node and route selection are presented. The performance of EASARA is validated through simulation. Simulation results demonstrate the performance supremacy of EASARA over contemporary scheme in terms of various metrics.


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