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Dependency-Aware Parallel Offloading and Computation in MEC-Enabled Networks
DOI:10.1109/LCOMM.2022.3142419.png)
摘要
En 中文
This letter proposes an effective dependency-aware subtask offloading and computation scheme in mobile edge computing (MEC) enabled networks, where we construct sequential execution windows of the MEC server by incorporating the hybrid dependencies among subtasks of an application, and the subtasks within the same subtask execution window could be offloaded and computed in parallel. By doing so, the completion delay and energy consumption of the application can be reduced. To make the proposed scheme achieve the minimum completion delay and energy consumption, we further jointly optimize the transmission rate and start execution time of subtasks within each execution window. The formulated problem is non-convex and difficult to solve. To make it tractable, we design a bisection search and successive convex approximation based iterative algorithm. Simulation results validate that compared with other existing schemes, our proposed scheme could reduce the summation of the completion delay and energy consumption by 10.36%.
Keyword:
Delays
Servers
Energy consumption
Costs
Optimization
Array signal processing
Task analysis
Hybrid-dependency
mobile edge computing
parallel offloading and computation
期刊
IF:
4.4
论文数:
1.3W
被引数:
2.2W
机构
引用论文
Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks多服务器移动边缘计算网络的联合任务卸载和资源分配
Robust Computation Offloading and Resource Scheduling in Cloudlet-Based Mobile Cloud Computing基于Cloudlet的移动云计算中健壮的计算卸载和资源调度

