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首页> 外文期刊>Concurrency and computation: practice and experience >Optimizing thin client caches for mobile cloud computing: Design space exploration using genetic algorithms
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Optimizing thin client caches for mobile cloud computing: Design space exploration using genetic algorithms

机译:为移动云计算优化瘦客户端缓存:使用遗传算法设计空间探索

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The emergence and rapid spread of interest and use of cloud computing as an accessible and expandable, as needed, computingfacility on the go, has a very deep affinity to the proliferation of intelligent mobile devices including smartphones and tablets. Together, these technologies have the potential of not leaving anybody behind when it comes to computing applications whether small and personal or large and organizational, and regardless of geographic boundaries and economical conditions. However, many technical challenges still exist that are still delaying the realization of this dream with the responsiveness and quality needed from the user perspective. In this paper, we examine user requirements for access to the cloud through thin clients, handheld and mobile devices. In light of these requirements we characterize some of the needed research developments particularly in the area of device architecture. We present our work in exploring the cache design space for embedded processors using evolutionary techniques for mobile and thin client processors. We present a heuristic, evolutionary approach (genetic algorithm) to explo­ration that significantly cuts down on the time and resources, obtaining a near optimal design. We demonstrate the real-world utility of our tool-chain?"CERE" (pronounced SIRI) short for (CachE Recommendation Engine)?by rapidly and efficiently designing a cache hierarchy, which maxi­mizes the performance of a web browser navigating to a set of popular websites running on a single ARM core. The goal is to improve the users' experience using web browsers. "CERE" made the right choices, and we were able to observe a 17.1% speedup going from the "best" hierarchy relative to the "worst" hierarchy. We will detail potential future directions as well.
机译:兴趣的出现和迅速扩散以及将云计算作为可访问的和可扩展的(按需提供)移动计算功能的使用,对智能手机(包括智能手机和平板电脑)的普及具有深厚的亲和力。总之,这些技术在计算应用程序方面(不论大小,个人或大型和组织性),并且不受地理边界和经济条件的影响,都有可能不让任何人落后。但是,仍然存在许多技术挑战,这些挑战仍在延迟实现该梦想的过程,而从用户角度而言,它具有所需的响应能力和质量。在本文中,我们研究了通过瘦客户端,手持设备和移动设备访问云的用户需求。根据这些要求,我们描述了一些必要的研究进展,特别是在设备架构领域。我们介绍了我们的工作,它使用针对移动和瘦客户端处理器的演进技术探索嵌入式处理器的缓存设计空间。我们提出了一种启发式,进化的方法(遗传算法)进行探索,可显着减少时间和资源,从而获得接近最佳的设计。我们通过快速有效地设计缓存层次结构,展示了我们的工具链“ CERE”(发音为SIRI)(CachE推荐引擎的缩写)的真实实用程序,该层次结构可最大化浏览到一组Web浏览器的Web浏览器的性能。在单个ARM内核上运行的流行网站。目的是改善使用Web浏览器的用户体验。 “ CERE”做出了正确的选择,从“最佳”层次相对于“最坏”层次,我们可以观察到17.1%的提速。我们还将详细说明潜在的未来方向。

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