Name
Abstract | ||
|---|---|---|
Driven by the tremendous in vehicular networks computation-intensive application demands, the incorporation of mobile edge computing (MEC) and vehicular cloud is convinced as a promising paradigm to fulfill computation offloading requirements. However, the changing vehicular communication topology (CVCT) poses a significant challenge for offloading directed acyclic graph (DAG) model application. Due to the precedence and connection constraint between different sub-jobs, the successful offloading of DAG-enabled apllication will be disturbed even interrupted without considering CVCT. To address this problem, we propose a topology-aware dynamic computaion offloading mechanism and adopt simulated annealing algorithm (TASA) to jointly optimize the energy consumption and completion time under dynamic environment, while guaranteeing the convergence of the proposed method. Simulation results reveal the effectiveness of the proposed method in overcoming CVCT's influence. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/VTC2021-Spring51267.2021.9448794 | 2021 IEEE 93RD VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-SPRING) |
Keywords | DocType | Citations |
Vehicular networks, mobile edge computing, vehicle mobility, communication topology, dynamic computation offloading | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhang Liu | 1 | 0 | 0.34 |
| Zhibin Gao | 2 | 0 | 0.34 |
| Minghui LiWang | 3 | 0 | 0.34 |
| Fangzhe Chen | 4 | 0 | 0.34 |
| Yilin Wang | 5 | 0 | 1.69 |
| Lianfen Huang | 6 | 0 | 0.34 |
| Yuliang Tang | 7 | 120 | 20.96 |