Mobile-edge computing casts the computation-intensive and delay-sensitive applications of mobile devices onto network edges.Task offloading incurs extra communication latency and energy cost,and extensive efforts have...Mobile-edge computing casts the computation-intensive and delay-sensitive applications of mobile devices onto network edges.Task offloading incurs extra communication latency and energy cost,and extensive efforts have focused on offloading schemes.Many metrics of the system utility are defined to achieve satisfactory quality of experience.However,most existing works overlook the balance between throughput and fairness.This study investigates the problem of finding an optimal offloading scheme in which the objective of optimization aims to maximize the system utility for leveraging between throughput and fairness.Based on Karush-Kuhn-Tucker condition,the expectation of time complexity is analyzed to derive the optimal scheme.A gradient-based approach for utility-aware task offloading is given.Furthermore,we provide an increment-based greedy approximation algorithm with 1+1/(e-1)ratio.Experimental results show that the proposed algorithms can achieve effective performance in utility and accuracy.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.61602084,61761136019,U1808206,61772112,and 61972083)the Post-Doctoral Science Foundation of China(No.2016M600202)+1 种基金the Doctoral Scientific Research Foundation of Liaoning Province(No.201601041)the Fundamental Research Fund for the Central Universities(No.DUT19JC53)。
文摘Mobile-edge computing casts the computation-intensive and delay-sensitive applications of mobile devices onto network edges.Task offloading incurs extra communication latency and energy cost,and extensive efforts have focused on offloading schemes.Many metrics of the system utility are defined to achieve satisfactory quality of experience.However,most existing works overlook the balance between throughput and fairness.This study investigates the problem of finding an optimal offloading scheme in which the objective of optimization aims to maximize the system utility for leveraging between throughput and fairness.Based on Karush-Kuhn-Tucker condition,the expectation of time complexity is analyzed to derive the optimal scheme.A gradient-based approach for utility-aware task offloading is given.Furthermore,we provide an increment-based greedy approximation algorithm with 1+1/(e-1)ratio.Experimental results show that the proposed algorithms can achieve effective performance in utility and accuracy.
