Applying differential evolution algorithm to deal with optimal path issues in wireless sensor networks

2015 ◽  
Author(s):  
Jingjuan Ren ◽  
Jiuwei Wang ◽  
Yulong Xu ◽  
Li Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Differential Evolution ◽  
Optimal Path ◽  
Differential Evolution Algorithm ◽  
Wireless Sensor ◽  
Evolution Algorithm

scholarly journals Differential Evolution Algorithm with Diversified Vicinity Operator for Optimal Routing and Clustering of Energy Efficient Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Subramaniam Sumithra ◽  
T. Aruldoss Albert Victoire
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Routing Problem

Due to large dimension of clusters and increasing size of sensor nodes, finding the optimal route and cluster for large wireless sensor networks (WSN) seems to be highly complex and cumbersome. This paper proposes a new method to determine a reasonably better solution of the clustering and routing problem with the highest concern of efficient energy consumption of the sensor nodes for extending network life time. The proposed method is based on the Differential Evolution (DE) algorithm with an improvised search operator called Diversified Vicinity Procedure (DVP), which models a trade-off between energy consumption of the cluster heads and delay in forwarding the data packets. The obtained route using the proposed method from all the gateways to the base station is comparatively lesser in overall distance with less number of data forwards. Extensive numerical experiments demonstrate the superiority of the proposed method in managing energy consumption of the WSN and the results are compared with the other algorithms reported in the literature.

scholarly journals Optimization of Wireless Sensor Networks Based on Differential Evolution Algorithm

2019 ◽  
Vol 15 (01) ◽  
pp. 183 ◽  
Author(s):  
Qing Wan ◽  
Ming-Jiang Weng ◽  
Song Liu
Keyword(s):  
Differential Evolution ◽  
Optimization Model ◽  
Optimization Problem ◽  
Optimal Path ◽  
Minimum Energy ◽  
Differential Evolution Algorithm ◽  
Path Optimization ◽  
Wireless Sensor ◽  
Advantages And Disadvantages ◽  
Evolution Algorithm

To study the optimization problem of wireless sensor network (WSN) based on differential evolution, the single objective differential evolution algorithm is applied and combined with the advantages and disadvantages crossover strategy. Firstly, the path optimization problem in WSN is analyzed, and the optimization model is established. Then, the differential evolution algorithm is used as the search tool to solve the minimum energy consumption in the path optimization model, that is, the optimal path problem. Finally, the comparison experiment is carried out on the classical algorithm genetic algorithm (GA), particle swarm optimization (PSO) and standard differential evolution (DE) algorithm. The results show that the performance of differential evolution algorithm based on crossover strategy is superior to or not worse than that of several contrast algorithms. It can be seen that the differential evolution algorithm based on advantage and disadvantage crossover strategy has good effectiveness.

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