Name
Abstract | ||
|---|---|---|
Mobile edge computing (MEC) is a promising approach that can reduce the latency of task processing by offloading tasks from user equipments (UEs) to MEC servers. Existing works always assume that the MEC server is capable of executing the offloaded tasks, without considering the impact of improper load on task processing efficiency. In this article, we present a two-stage computing offloading scheme to minimize the task processing delay while managing the server load properly. To minimize the task processing delay, each UE optimizes how much workload to be offloaded to the MEC server. To improve the task processing efficiency of the server, we arrange the processing order of offloading tasks by introducing an aggregative game with an instantaneous load billing mechanism. The proposed game can obtain the optimal task offloading and processing strategy with limited information and a small number of iterations. Simulation results show that our scheme approaches the optimal offloading strategy in terms of minimizing task processing delay for each UE and improving processing efficiency for the server. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TSC.2020.2996764 | IEEE Transactions on Services Computing |
Keywords | DocType | Volume |
Mobile edge computing,computation offloading,aggregative game,instantaneous load billing | Journal | 15 |
Issue | ISSN | Citations |
3 | 1939-1374 | 2 |
PageRank | References | Authors |
0.36 | 33 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingjin Gao | 1 | 2 | 0.36 |
| Rujing Shen | 2 | 3 | 1.05 |
| Jun Li | 3 | 747 | 90.31 |
| Shihao Yan | 4 | 513 | 42.67 |
| Yonghui Li | 5 | 3393 | 253.70 |
| Jinglin Shi | 6 | 571 | 59.91 |
| Zhu Han | 7 | 11215 | 760.71 |
| Li Zhuo | 8 | 2 | 0.36 |