Caching Strategy for Scalable Lookup of Personal Content

摘要

Todayȁ9;s trend is to create and share personal content, such as music files, digital photos and digital movies. The result is an explosive growth of a userȁ9;s personal content archive. Managing such an often distributed collection becomes a complex and time consuming task, which indicates the need for a personal content management system that provides storage space transparently, is quality-aware, and is available at any time and at any place to end-users. A solution that fulfills this need is a Personal Content Storage Service (PCSS). A key feature of a PCSS is the ability to search worldwide through the dataset of personal files. Due to the extremely large size of the dataset of personal content, a centralized approach is no longer feasible; therefore the PCSS uses a structured peer-to-peer network: the Distributed Hash Table (DHT). In order to further increase the lookup performance, a caching layer is used between the application layer and the DHT. In this article we present the caching layer and introduce the Request Times Distance (RTD) caching algorithm, which uses popularity and distance metrics to increase the lookup performance. By extending the RTD algorithm with a sliding window and cooperative caching, a more efficient solution than standard algorithms is obtained. The cooperative RTD caching algorithm is evaluated using the PlanetSim simulation framework and shows a performance increase of up to 16% compared to the Least Frequently Used (LFU) caching algorithm.