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Distributed task offloading strategy to low load base stations in mobile edge computing environment

机译:分布式任务卸载到移动边缘计算环境中低负载基站的策略

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摘要

Due to the limited computing resources and battery capacity of existing mobile devices, it cannot meet the requirements of low load base station group for computing capacity and delay, and the emergence of mobile edge computing (MEC) technology provides the possibility for it. Therefore, a distributed task unloading strategy to low load base station group under MEC environment is proposed. Firstly, the communication resource, computing resource and task queue of low load base station group are modeled to quantify the energy cost in the process of task unloading. Then, the game theory is introduced, and the potential game model is used to solve the problem of distributed task unloading. The target function of energy optimization based on delay limitation is transformed into the potential game equation, and the mobile device selects MEC nodes according to the game results to calculate the unloading. Finally, based on the MATLAB platform, the algorithm is simulated, and the results show that the proposed potential game equation can converge to the Nash equilibrium. Compared with other algorithms, the proposed distributed task unloading algorithm can effectively save the energy consumption of task unloading.
机译:由于现有移动设备的计算资源和电池容量有限,因此无法满足低负载基站组的计算能力和延迟的要求,并且移动边缘计算(MEC)技术的出现提供了它的可能性。因此,提出了在MEC环境下向低负载基站组进行分布式任务卸载策略。首先,建模低负载基站组的通信资源,计算资源和任务队列以量化任务卸载过程中的能量成本。然后,介绍了博弈论,并且潜在的游戏模型用于解决分布式任务卸载问题。基于延迟限制的能量优化的目标功能转换为潜在的游戏等式,并且移动设备根据游戏结果选择MEC节点以计算卸载。最后,基于MATLAB平台,模拟算法,结果表明,所提出的潜在游戏等式可以收敛到纳什均衡。与其他算法相比,所提出的分布式任务卸载算法可以有效地节省了任务卸载的能量消耗。

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