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Time-Minimized Offloading for Mobile Edge Computing Systems
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DOI：10.1109/ACCESS.2019.2941825.png)
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Abstract
En 中文
Task offloading is the hot issue for current network. The rapid development of intelligent terminals brings new opportunity for offloading. This paper studies the problem of task offloading in a mobile edge computing system, where both the fixed devices with power supply of electricity and mobile terminals are computation resources. Considering tasks in an application are not independent, the task-dependency is introduced to describe the relationship of tasks. Then, the offloading details are analyzed to illustrate energy consumption and completion time during task assignment. Based on task-dependency and offloading process, the problem of task offloading is formulated to minimize the completion time of whole applications under energy and time constraints. Since it is the NP-hard problem, the heuristic offloading algorithm is proposed to assign tasks of whole applications. In the proposed algorithm, based on the task urgency, tasks of whole applications are assigned to chosen devices to achieve the low offloading cost during the initial assignment. To reduce the completion time, the relative remaining cost is introduced to reassign tasks under constraints. Simulation results illustrate that the proposed heuristic algorithm significantly reduces the completion time under system constraints.
Keywords:
Task analysis
Servers
Energy consumption
Program processors
Heuristic algorithms
Time factors
Delays
Completion time
offloading
edge
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