As a practical solution that could reduce the communication and computation load of central servers in digital factories,edge computing has been widely used in modern industry.In mobile edge computing,a reasonable off...As a practical solution that could reduce the communication and computation load of central servers in digital factories,edge computing has been widely used in modern industry.In mobile edge computing,a reasonable offloading strategy can balance the computation load and reduce the energy consumption of mobile devices,which is the key to optimizing network operation.In this paper,a Relative Position-based Bacterial Foraging Optimization algorithm with Dropout strategy,RPBFO-D,is proposed to optimize the computation offloading problem.A many-to-many relationship model of devices-tasks-servers is established,comprehensively considering the time delay and energy consumption,and RPBFO-D is proposed to solve the problem.In this algorithm,the structure and operators of the original BFO are redesigned,and the dropout strategy of the neural network maintains diversity.Experiments with parameter settings demonstrate the effectiveness of the dropout strategy.Results show that RPBFO-D has better convergence accuracy than comparison algorithms,which demonstrates that it is a competitive approach for computation offloading.展开更多
分析了细菌觅食优化(BFO)算法的原理以及当前的研究状况,主要根据心理学家爱德华·桑代克(E L Thordike)的经典效果律和经济学家巴莱多的巴莱多定律等对标准BFO算法存在的不足进行改进;将改进后的BFO算法在函数优化问题上进行仿真实...分析了细菌觅食优化(BFO)算法的原理以及当前的研究状况,主要根据心理学家爱德华·桑代克(E L Thordike)的经典效果律和经济学家巴莱多的巴莱多定律等对标准BFO算法存在的不足进行改进;将改进后的BFO算法在函数优化问题上进行仿真实验,实验结果表明改进后的BFO算法比标准BFO算法具有更快的收敛速度和更强的搜索性能。展开更多
基金supported in part by the Guangdong Basic and Applied Basic Research Foundation(Nos.2022A1515140093,2022A1515140035,2022A1515110924,and 2022A1515110501)the National Natural Science Foundation of China(Nos.72471060,52305550,and 52305097)+1 种基金the Guangdong S&T Program(No.2022B0303010001)the Dongguan Sci-tech Commissioner Program(No.20231800500112).
文摘As a practical solution that could reduce the communication and computation load of central servers in digital factories,edge computing has been widely used in modern industry.In mobile edge computing,a reasonable offloading strategy can balance the computation load and reduce the energy consumption of mobile devices,which is the key to optimizing network operation.In this paper,a Relative Position-based Bacterial Foraging Optimization algorithm with Dropout strategy,RPBFO-D,is proposed to optimize the computation offloading problem.A many-to-many relationship model of devices-tasks-servers is established,comprehensively considering the time delay and energy consumption,and RPBFO-D is proposed to solve the problem.In this algorithm,the structure and operators of the original BFO are redesigned,and the dropout strategy of the neural network maintains diversity.Experiments with parameter settings demonstrate the effectiveness of the dropout strategy.Results show that RPBFO-D has better convergence accuracy than comparison algorithms,which demonstrates that it is a competitive approach for computation offloading.
文摘分析了细菌觅食优化(BFO)算法的原理以及当前的研究状况,主要根据心理学家爱德华·桑代克(E L Thordike)的经典效果律和经济学家巴莱多的巴莱多定律等对标准BFO算法存在的不足进行改进;将改进后的BFO算法在函数优化问题上进行仿真实验,实验结果表明改进后的BFO算法比标准BFO算法具有更快的收敛速度和更强的搜索性能。
