Joint optimization of computing ratio and access points' density for mixed mobile edge/cloud computing

被引:3
作者
Jing, Tianqi [1 ]
He, Shiwen [2 ,3 ]
Yu, Fei [1 ]
Huang, Yongming [1 ]
Yang, Luxi [1 ]
Ren, Ju [2 ]
机构
[1] Southeast Univ, Sch Informat Sci & Engn, Southeast Univ Rd, Nanjing 210096, Peoples R China
[2] Cent South Univ, Sch Comp Sci & Engn, Lushan South Rd, Changsha 410083, Peoples R China
[3] Purple Mt Labs, Mozhou East Rd, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
Computation offloading; Mobile edge computing; Density allocation; Mode selection; RESOURCE-ALLOCATION; NETWORKS; SCENARIOS; RADIO;
D O I
10.1186/s13638-021-01891-w
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cooperation between the mobile edge computing (MEC) and the mobile cloud computing (MCC) in offloading computing could improve quality of service (QoS) of user equipments (UEs) with computation-intensive tasks. In this paper, in order to minimize the expect charge, we focus on the problem of how to offload the computation-intensive task from the resource-scarce UE to access point's (AP) and the cloud, and the density allocation of APs' at mobile edge. We consider three offloading computing modes and focus on the coverage probability of each mode and corresponding ergodic rates. The resulting optimization problem is a mixed-integer and non-convex problem in the objective function and constraints. We propose a low-complexity suboptimal algorithm called Iteration of Convex Optimization and Nonlinear Programming (ICONP) to solve it. Numerical results verify the better performance of our proposed algorithm. Optimal computing ratios and APs' density allocation contribute to the charge saving.
引用
收藏
页数:19
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