多用户优化卸载:在移动边缘云计算中利用移动性和资源分配

Hongyan Yu, Jiadi Liu, Songtao Guo
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引用次数: 3

摘要

移动云计算(Mobile cloud computing, MCC)作为一种有发展前景的计算范式,通过将计算密集型任务从资源受限的智能移动设备上转移到资源丰富的中心云上,可以显著提高智能移动设备的计算能力和节约能源。与中心云相比,边缘云可以以更低的延迟为附近的smd提供服务。然而,边缘云可能是移动的,其资源仅限于附近的多个用户。在本文中,我们的目标是通过在边缘云计算(ECC)系统中将计算从smd卸载到边缘云来最小化多个设备的总执行成本。考虑到smd和边缘云的移动性,我们首先在smd和边缘云的应用完成时间和连接时间约束下,以及边缘云和smd的计算资源有限的情况下,提出了总成本最小化问题。然后,通过求解最小化问题,提出了基于博弈模型的最优卸载选择策略和边缘云收益竞争算法,将边缘云资源最优地分配给smd,以实现最小的总执行成本。实验结果表明,与现有方法相比,我们的卸载策略可以有效地降低能耗和应用完成时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-User Optimal Offloading: Leveraging Mobility and Allocating Resources in Mobile Edge Cloud Computing
Mobile cloud computing (MCC), as a prospective computing paradigm, can significantly enhance computation capability and save energy of smart mobile devices (SMDs) by offloading computation-intensive tasks from resource-constrained SMDs onto the resource-rich center cloud. Compared to a center cloud, an edge cloud can provide services to nearby SMDs with lower latency. However, the edge cloud may be mobile and its resources are limited to multiple nearby users. In this paper, we aim to minimize the total execution cost of multiple devices by offloading the computation from SMDs onto edge clouds in an edge cloud computing (ECC) system. By considering the mobility of SMDs and edge clouds, we first formulate the total cost minimization problem under the constraints of application completion deadline and connection time between SMDs and edge clouds as well as the limited computing resource of both edge clouds and SMDs. Then, by solving the minimization problem, we propose an optimal offloading selection strategy based on a game model, and an edge cloud payoff competition algorithm to optimally allocate edge cloud resource to SMDs to achieve the minimum total execution cost. Experimental results show that our offloading strategy can effectively reduce energy consumption and application completion time compared with the state-of-the-art methods.
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