CoOMO:具有多站点卸载的移动边缘服务的成本效益计算外包

Tianhui Meng, Huaming Wu, Zhihao Shang, Yubin Zhao, Cheng-Zhong Xu
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引用次数: 0

摘要

手机和平板电脑正在成为首选的平台。然而,这些系统仍然受到有限的电池和计算资源的影响。移动边缘系统中的一种流行技术是计算外包,它通过将繁重的工作负载迁移到位于蜂窝网络边缘的资源丰富的云来增强移动系统的功能。在多站点场景中,移动设备可以通过卸载到多个云服务提供商来节省更多的时间和能源。最重要的挑战之一是如何选择服务器来卸载作业。本文考虑了一个多站点决策问题。提出了一种确定双站点移动边缘计算系统中适当分配概率的方案。提出了一种双服务器卸载系统的开放排队网络模型,并提出了用于评估该系统的性能指标。然后在移动棋局的具体场景中,在数据传输量较小但计算量较大的情况下,我们进行了卸载实验,获得模型参数。给定到达率和服务率等参数,我们计算分配任务卸载或本地执行的最佳概率,以及选择不同云服务器的最佳概率。分析结果证实了我们的多站点卸载方案在响应时间和能源使用方面是有益的。此外,还对系统到达率进行了敏感性分析,以调查参数值变化的更广泛影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CoOMO: Cost-efficient Computation Outsourcing with Multi-site Offloading for Mobile-Edge Services
Mobile phones and tablets are becoming the primary platform of choice. However, these systems still suffer from limited battery and computation resources. A popular technique in mobile edge systems is computing outsourcing that augments the capabilities of mobile systems by migrating heavy workloads to resourceful clouds located at the edges of cellular networks. In the multi-site scenario, it is possible for mobile devices to save more time and energy by offloading to several cloud service providers. One of the most important challenges is how to choose servers to offload the jobs. In this paper, we consider a multi-site decision problem. We present a scheme to determine the proper assignment probabilities in a two-site mobile-edge computing system. We propose an open queueing network model for an offloading system with two servers and put forward performance metrics used for evaluating the system. Then in the specific scenario of a mobile chess game, where the data transmission is small but the computation jobs are relatively heavy, we conduct offloading experiments to obtain the model parameters. Given the parameters as arrival rates and service rates, we calculate the optimal probability to assign jobs to offload or locally execute and the optimal probabilities to choose different cloud servers. The analysis results confirm that our multi-site offloading scheme is beneficial in terms of response time and energy usage. In addition, sensitivity analysis has been conducted with respect to the system arrival rate to investigate wider implications of the change of parameter values.
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