The WSN(wireless sensor network)node optimization problem faces the challenge of efficient deployment and adaptation under limited resources and a dynamically changing environment.The complex and changing deployment e...The WSN(wireless sensor network)node optimization problem faces the challenge of efficient deployment and adaptation under limited resources and a dynamically changing environment.The complex and changing deployment environment puts higher requirements on the search space,computational cost,and optimization efficiency of the algorithms.For this reason,a slime mould algorithm called SCA-SMA is proposed to solve the above problem.In SCA-SMA,a reverse Sobol sequence is used to initialize the population to increase the population diversity and improve the probability of approaching the optimal solution.To better balance local exploitation and global exploration,a dynamic selection of sine cosine update mechanism is proposed:using an optimal position selection mechanism in the global exploration phase to avoid local optima,and integrating the sine cosine algorithm in the local exploitation phase to improve the mucilage position update method,enrich the optimization search process and enhance the development capability of the algorithm.Finally,an adaptive mutation strategy can be proposed to increase the search range of the algorithm and motivate SCA-SMA to explore more promising regions.To evaluate the performance of the algorithm,SCA-SMA is experimentally validated in five different aspects.The results show that SCA-SMA is significantly competitive compared to advanced MAs.In particular,in facing the WSN node coverage problem,SCA-SMA has more obvious advantages in both average coverage and optimal coverage,which makes it possible to fully utilize the sensing range of each sensor node,while avoiding the waste of resources and the generation of monitoring blind zones.展开更多
基金supported by special project of the National Natural Science Foundation of China[No.42027806]special Fund of the National Natural Science Foundation of China[No.42041006]+3 种基金the National Key Research and Development Program Project of China[No.2018YFC1504705]the Key Program of the National Natural Science Foundation of China[No.61731015]the major instrument,the project of Natural Science Foundation in Shaanxi Province[No.2018JM6029]the Key Research and Development Program of Shaanxi[No.2022GY-331].
文摘The WSN(wireless sensor network)node optimization problem faces the challenge of efficient deployment and adaptation under limited resources and a dynamically changing environment.The complex and changing deployment environment puts higher requirements on the search space,computational cost,and optimization efficiency of the algorithms.For this reason,a slime mould algorithm called SCA-SMA is proposed to solve the above problem.In SCA-SMA,a reverse Sobol sequence is used to initialize the population to increase the population diversity and improve the probability of approaching the optimal solution.To better balance local exploitation and global exploration,a dynamic selection of sine cosine update mechanism is proposed:using an optimal position selection mechanism in the global exploration phase to avoid local optima,and integrating the sine cosine algorithm in the local exploitation phase to improve the mucilage position update method,enrich the optimization search process and enhance the development capability of the algorithm.Finally,an adaptive mutation strategy can be proposed to increase the search range of the algorithm and motivate SCA-SMA to explore more promising regions.To evaluate the performance of the algorithm,SCA-SMA is experimentally validated in five different aspects.The results show that SCA-SMA is significantly competitive compared to advanced MAs.In particular,in facing the WSN node coverage problem,SCA-SMA has more obvious advantages in both average coverage and optimal coverage,which makes it possible to fully utilize the sensing range of each sensor node,while avoiding the waste of resources and the generation of monitoring blind zones.
