Zijie Li
ABSTRACT
Mobile edge computing (MEC) can alleviate computation and power limitation of user equipments (UEs) by offloading tasks to MEC servers or the remote cloud. Delays of finishing tasks are the most important indicators for a MEC system. However, existing researches in MEC on task allocation problems are decided by UEs or by centralized algorithms, imposing burden to UEs or centralize controllers. Most of them neglect real-time resource utilization of MEC system, which may affect the performance of executing offloaded tasks. To address the above problems, we propose a distributed game-theoretic task-offloading allocation (GTOA) algorithm by transforming a task allocation problem into a strategy game, turning the goal of maximizing deadline satisfaction and resource usage into a payoff function, which MEC server is eager to obtain. Simulations with a different number of MEC servers of system handling tasks for UEs showed that the algorithm can improve system resource utilization while meeting delay limit of most offloaded tasks.
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Index Terms
- Delay-guaranteed Task Allocation in Mobile Edge Computing with Balanced Resource Utilization
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