With advances in wireless communication technology, more and more people depend heavily on portable mobile devices for business, entertainments and social interactions. This poses a great challenge of building a seamless application experience across different computing platforms. A key issue is the resource limitations of mobile devices due to their portable size, however this can be overcome by offloading computation-intensive tasks from the mobile devices to clusters of nearby computers called cloudlets through wireless access points. As increasing numbers of people access the Internet via mobile devices, it is reasonable to envision in the near future that cloudlet services will be available for the public through easily accessible public wireless metropolitan area networks (WMANs). However, the outdated notion of treating cloudlets as isolated data-centers-in-boxes must be discarded as there are clear benefits to connecting multiple cloudlets together to form a network. In this paper we investigate how to balance the workload among cloudlets in an WMAN to optimize mobile application performance. We first introduce a novel system model to capture the response time delays of offloaded tasks and formulate an optimization problem with the aim to minimize the maximum response time of all offloaded tasks. We then propose two algorithms for the problem: one is a fast heuristic, and another is a distributed genetic algorithm that is capable of delivering a more accurate solution compared with the first algorithm, but at the expense of a much longer running time. We finally evaluate the performance of the proposed algorithms in realistic simulation environments. The experimental results demonstrate the significant potential of the proposed algorithms in reducing the user task response time, maximizing user experience.

中文翻译：

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无线城域网中QoS感知的Cloudlet负载均衡

随着无线通信技术的进步，越来越多的人严重依赖便携式移动设备进行商务、娱乐和社交互动。这对构建跨不同计算平台的无缝应用体验提出了巨大挑战。一个关键问题是移动设备由于其便携尺寸而存在资源限制，但是这可以通过将计算密集型任务从移动设备卸载到附近称为 cloudlets 的计算机集群来克服。随着越来越多的人通过移动设备访问 Internet，可以合理地设想在不久的将来，公众将可以通过易于访问的公共无线城域网 (WMAN) 来获得 Cloudlet 服务。然而，必须摒弃将小云视为孤立的盒内数据中心的过时观念，因为将多个小云连接在一起形成网络有明显的好处。在本文中，我们研究了如何在 WMAN 中平衡小云之间的工作负载以优化移动应用程序性能。我们首先引入了一种新的系统模型来捕获卸载任务的响应时间延迟，并制定优化问题，旨在最小化所有卸载任务的最大响应时间。然后，我们针对该问题提出了两种算法：一种是快速启发式算法，另一种是分布式遗传算法，与第一种算法相比，它能够提供更准确的解决方案，但代价是运行时间要长得多。我们最终评估了所提出算法在现实模拟环境中的性能。实验结果证明了所提出的算法在减少用户任务响应时间、最大化用户体验方面的巨大潜力。