Joint Computation Offloading and Resource Allocation for Mobile-Edge Computing Assisted Ultra-Dense Networks

被引:0
|
作者
Gao Y. [1 ,2 ]
Zhang H. [1 ,3 ]
Yu F. [1 ,3 ]
Xia Y. [1 ,2 ]
Shi Y. [1 ,2 ]
机构
[1] School of Physics and Electronic Information, Luoyang Normal University, Luoyang
[2] Henan Key Laboratory for Big Data Processing and Analytics of Electronic Commerce, Luoyang Normal University, Luoyang
[3] School of Communications and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an
关键词
mobile-edge computing (MEC); power allocation; task offloading; ultra-dense networks (UDN);
D O I
10.23919/JCIN.2022.9745485
中图分类号
学科分类号
摘要
Mobile-edge computing (MEC), enabling to offload computing tasks on mobile devices towards edge servers, can reduce the terminals cost. However, a single MEC sever usually has limited computing capabilities, which can not meet a large number of terminals’ requirements. In this paper, we consider an ultra-dense networks (UDN) scenario where the macro base stations (MBSs) are assisted by MEC severs. In particular, we first construct system model for MEC assisted UDN, and build the system overhead minimization. Next, in order to solve the problem, we transform the problem into three sub-problems, i.e., offloading strategies subproblem, channel assignments subproblem, and power allocation subproblem. Then, employing joint offloading and resource allocation algorithms, we obtain the optimal joint strategy for the MEC assisted UDNs. Finally, simulations are conducted to evaluate the performance of our proposed algorithms. Numerical results show that obtained algorithms can effectively reduce the energy consumption of the system and improve the overall performance of the system. © 2022, Posts and Telecom Press Co Ltd. All rights reserved.
引用
收藏
页码:96 / 106
页数:10
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