D2D-Assisted Multi-User Cooperative Partial Offloading, Transmission Scheduling and Computation Allocating for MEC

被引:58
作者
Peng, Jie [1 ]
Qiu, Hongbing [2 ]
Cai, Jun [3 ]
Xu, Wenjun [4 ]
Wang, Junyi [2 ]
机构
[1] Xidian Univ, Sch Telecommun Engn, Xian 710071, Peoples R China
[2] Guilin Univ Elect Technol, Sch Informat & Commun, Guilin 541004, Peoples R China
[3] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada
[4] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
基金
中国国家自然科学基金;
关键词
Device-to-device communication; Relays; Cloud computing; Processor scheduling; Wireless communication; Uplink; Dynamic scheduling; Mobile edge computing; D2D communication; partial offloading; cooperative scheduling; computation allocating; RESOURCE-ALLOCATION; MOBILE;
D O I
10.1109/TWC.2021.3062616
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
By fully exploiting the cooperative communication capacities among mobile terminals (MTs), the MTs can adapt the offloading designs well to the practical network with dynamic features. In this paper, joint multi-user cooperative partial offloading, transmission scheduling and computation allocating is discussed for device-to-device (D2D) underlay mobile edge computing (MEC). By considering stochastic application requests, unpredictable MTs states, time-varying channel states and computation resources, a customized application offloading model, which aims to minimize the network-wide response latency and energy consumption simultaneously, is formulated. In order to solve this non-convex and non-smooth optimization problem, an online resource coordinating and allocating scheme (ORCAS) is proposed by exploiting Lyapunov optimization theory, variable substitution technique and resource provisioning priority mechanism. Both theoretical analyses and simulation results demonstrate that the proposed ORCAS can 1) drive the application response cost converge to the minimum; 2) achieve superior performance (e.g., the average network-wide response cost under ORCAS is approximately 19.14% lower than that under partial offloading directly); 3) adapt to dynamic situations in terms of stochastic user demands and channel states.
引用
收藏
页码:4858 / 4873
页数:16
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