论文标题
PackCache：云中的一种在线成本驱动的数据缓存算法
PackCache: An Online Cost-driven Data Caching Algorithm in the Cloud
论文作者
论文摘要
在本文中，我们在云环境中研究了一个数据缓存问题，其中可以将多个经常共同利用的数据项包装为单个项目被转移，以动态地服务一系列数据请求，并降低成本。为此，我们提出了一种关于均质成本模型（称为PackCache）的在线算法，该算法可以利用FP-Tree技术来挖掘那些经常共同利用的数据项来包装，从而可以通过利用预期的缓存概念来在线提供成本效益。我们显示该算法是2αcompetitive，在研究的缓存问题上，任何确定性的在线算法都达到了竞争比率的下限，并且还达到了服务请求的时间和空间效率。最后，我们通过实验研究评估算法的性能，以显示其实际的成本效益和可扩展性。
In this paper, we study a data caching problem in the cloud environment, where multiple frequently co-utilised data items could be packed as a single item being transferred to serve a sequence of data requests dynamically with reduced cost. To this end, we propose an online algorithm with respect to a homogeneous cost model, called PackCache, that can leverage the FP-Tree technique to mine those frequently co-utilised data items for packing whereby the incoming requests could be cost-effectively served online by exploiting the concept of anticipatory caching. We show the algorithm is 2αcompetitive, reaching the lower bound of the competitive ratio for any deterministic online algorithm on the studied caching problem, and also time and space efficient to serve the requests. Finally, we evaluate the performance of the algorithm via experimental studies to show its actual cost-effectiveness and scalability.
