Offloading Schemes in Mobile Edge Computing With an Assisted Mechanism

被引:6
作者
Wang, Haojia [1 ]
Peng, Zhangyou [1 ]
Pei, Yongsheng [1 ]
机构
[1] Shanghai Univ, Key Lab Specialty Fiber Opt & Opt Access Networks, Shanghai 200444, Peoples R China
关键词
Mobile handsets; Task analysis; Servers; Edge computing; Resource management; Optimization; Cloud computing; Assisted mechanism; computation offloading scheme; mobile edge computing; resource allocation; RESOURCE-ALLOCATION; CLOUD;
D O I
10.1109/ACCESS.2020.2979770
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile edge computing (MEC) is a promising paradigm for providing computing and storage capabilities in close proximity to mobile devices. To solve the scenario in which massive mobile devices have tasks to be processed at the same time, this paper proposes an assisted mechanism for the MEC system. When the primary MEC server is unable to meet the delay requirements of the mobile devices within its coverage area, a portion of the tasks can be offloaded to secondary MEC servers to obtain extra resources for processing. This MEC framework effectively reduces the computing and communication burden of the primary MEC server and improves the resource utilization of the secondary MEC servers. To maximize the system offloading utility in terms of latency, we formulated an optimization problem that jointly optimizes the task assignment, computing resource allocation and offloading decision of all mobile devices. Since the formulated problem is a mixed integer nonlinear problem, we use the decomposition method to convert the optimization problem into several subproblems. In addition, a heuristic algorithm based on the priorities of mobile devices and the MEC servers is proposed to obtain the suboptimal device offloading strategy. The numerical results show that the assisted mechanism can effectively reduce system latency and improve system reliability. In addition, the performance of our proposed algorithm is close to the optimal solution.
引用
收藏
页码:50721 / 50732
页数:12
相关论文
共 36 条
[1]  
[Anonymous], 2014, Convex Optimiza- tion
[2]  
[Anonymous], 2012, P 2012 ACMIEEE INT S
[3]   Toward Interconnected Virtual Reality: Opportunities, Challenges, and Enablers [J].
Bastug, Ejder ;
Bennis, Mehdi ;
Medard, Muriel ;
Debbah, Merouane .
IEEE COMMUNICATIONS MAGAZINE, 2017, 55 (06) :110-117
[4]   Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing [J].
Chen, Xu ;
Jiao, Lei ;
Li, Wenzhong ;
Fu, Xiaoming .
IEEE-ACM TRANSACTIONS ON NETWORKING, 2016, 24 (05) :2827-2840
[5]   Decentralized Computation Offloading Game for Mobile Cloud Computing [J].
Chen, Xu .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2015, 26 (04) :974-983
[6]  
Cheng K, 2018, IEEE ICC
[7]   Joint Computation Offloading and User Association in Multi-Task Mobile Edge Computing [J].
Dai, Yueyue ;
Xu, Du ;
Maharjan, Sabita ;
Zhang, Yan .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (12) :12313-12325
[8]  
Ge XH, 2016, IEEE WIREL COMMUN, V23, P72, DOI 10.1109/MWC.2016.7422408
[9]  
He YH, 2019, IEEE ICC
[10]   D2D Communications Meet Mobile Edge Computing for Enhanced Computation Capacity in Cellular Networks [J].
He, Yinghui ;
Ren, Jinke ;
Yu, Guanding ;
Cai, Yunlong .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2019, 18 (03) :1750-1763