使用ThinkAir释放移动云计算的力量
Unleashing the Power of Mobile Cloud Computing using ThinkAir
摘要：
智能手机近年来大受欢迎，变得越来越复杂和强大。因此，世界各地的开发人员正在构建越来越复杂的应用程序，这些应用程序需要越来越多的计算能力和能量。在本文中，我们提出了ThinkAir，一个框架，使开发人员可以简单地将他们的智能手机应用程序迁移到云。ThinkAir在云中利用智能手机虚拟化的概念，并提供方法级计算卸载。在以往工作的基础上，它侧重于服务器端的弹性和可扩展性，并通过使用多个虚拟机（VM）映像并行化方法执行来增强移动云计算的能力。我们使用一系列基准测试来评估系统，从简单的微基准测试到更复杂的应用程序。首先，我们表明，执行时间和能源消耗减少了两个数量级的N皇后难题和一个数量级的人脸检测和病毒扫描应用程序，使用云卸载。然后，我们表明，如果一个任务是并行的，用户可以请求多个虚拟机来执行它，这些虚拟机将动态提供。事实上，通过利用并行化，我们实现了对以前的应用程序的执行时间和能源消耗更大的减少。最后，我们使用一个内存消耗的图像组合器工具来证明，应用程序可以动态地请求具有更多计算能力的虚拟机，以满足其计算需求。
英文摘要：
Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable. As a result, developers worldwide are building increasingly complex applications that require ever increasing amounts of computational power and energy. In this paper we propose ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud. ThinkAir exploits the concept of smartphone virtualization in the cloud and provides method level computation offloading. Advancing on previous works, it focuses on the elasticity and scalability of the server side and enhances the power of mobile cloud computing by parallelizing method execution using multiple Virtual Machine (VM) images. We evaluate the system using a range of benchmarks starting from simple micro-benchmarks to more complex applications. First, we show that the execution time and energy consumption decrease two orders of magnitude for the N-queens puzzle and one order of magnitude for a face detection and a virus scan application, using cloud offloading. We then show that if a task is parallelizable, the user can request more than one VM to execute it, and these VMs will be provided dynamically. In fact, by exploiting parallelization, we achieve a greater reduction on the execution time and energy consumption for the previous applications. Finally, we use a memory-hungry image combiner tool to demonstrate that applications can dynamically request VMs with more computational power in order to meet their computational requirements.
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