[1]WANG Gong,SUN Mingyang,SUN Huiyang,et al.An Adaptive Pheromone Evaporation Coefficient Based Ant Colony Routing Algorithm for Wireless Sensor Networks[J].Journal of Zhengzhou University (Engineering Science),2022,43(01):41-47.
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
43卷
Number of periods:
2022 01
Page number:
41-47
Column:
Public date:
2022-01-09
- Title:
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An Adaptive Pheromone Evaporation Coefficient Based Ant Colony Routing Algorithm for Wireless Sensor Networks
- Author(s):
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WANG Gong1; SUN Mingyang1; SUN Huiyang2; TENG Ziming3
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1.School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China;
2.Department of Cryptographic Science and Technology, Beijing Electronic Science and Technology Institute, Beijing 100070, China; 3.College of Communication Engineering, Jilin University, Changchun 130012, China
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- Keywords:
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wireless sensor network; loop effect; adaptive pheromone evaporation coefficient; routing; node energy
- CLC:
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TP393
- DOI:
-
-
- Abstract:
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At present, the ant colony loop phenomenon and uneven energy distribution of nodes in the wireless sensor networks could cause nodes to go dormant prematurely and shorten the network lifetime. To improve the accuracy of the pheromone update formula and further balance nodes energy consumption, the following improvements could be made based on the original ant colony algorithm: add data into ant data packet, such as the sequence number of the forward ant data packet, the source address on the packet of the forward ant, number of packet path nodes, energy consumed by relay nodes, length of path, survival time of the ant data packet, initial energy and average remaining energy of packet. The adaptive evaporation coefficient could be introduced into the pheromone update formula whose number of routing hops was altered to the energy consumption of multiple hops; the pheromone increment formula could be improved, the number of nodes visited by packets was redefined as the node energy loss function. In experimental results, there was a 5.7 percent reduce in the shortest path. It was obvious that this algorithm could effectively mitigate the ant loop effect, ba-lance nodes energy consumption and extend the network lifetime.