基于云的、以用户为中心的移动应用优化

Jack Kolb, Prashant Chaudhary, Alexander Schillinger, A. Chandra, J. Weissman
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引用次数: 3

摘要

云中可用的大量计算和存储资源使其非常适合解决移动设备的限制。基于对用户活动的分析,我们探索使用云基础设施来优化以内容为中心的移动应用程序,这些应用程序可能具有很高的通信和存储要求。我们提出了两种特定的优化,预取和预取,以及一个中间件框架的设计和实现,该框架允许移动应用程序开发人员轻松地利用这些技术。我们的框架完全适用于任何以内容为中心的移动应用程序,这是一个庞大且不断增长的互联网应用程序类别。使用新闻聚合应用程序作为案例研究来评估我们的实现。我们使用余弦相似度方案来识别具有相似兴趣的用户,这反过来又用于确定要预取的内容。还考虑了为我们的框架实现的各种缓存算法。工作负载跟踪和模拟用于度量应用程序和框架的性能。我们观察到,由于使用了我们的框架,应用程序的性能有了很大的提高,开销也很合理。我们的系统还显著优于在不考虑用户活动的情况下执行相同优化的基线实现。
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Cloud-Based, User-Centric Mobile Application Optimization
The abundance of compute and storage resources available in the cloud makes it well-suited to addressing the limitations of mobile devices. We explore the use of cloud infrastructure to optimize content-centric mobile applications, which can have high communication and storage requirements, based on the analysis of user activity. We present two specific optimizations, precaching and prefetching, as well as the design and implementation of a middleware framework that allows mobile application developers to easily utilize these techniques. Our framework is fully generalizable to any content-centric mobile application, a large and growing class of Internet applications. A news aggregation application is used as a case study to evaluate our implementation. We make use of a cosine similarity scheme to identify users with similar interests, which in turn is used to determine what content to prefetch. Various cache algorithms, implemented for our framework, are also considered. A workload trace and simulation are used to measure the performance of the application and framework. We observe a dramatic improvement in application performance due to use of our framework with a reasonable amount of overhead. Our system also significantly outperforms a baseline implementation that performs the same optimizations without taking user activity into account.
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