Cache Design for Massive Heterogeneous Data of Mobile Social Media

Since social media gains ever increasing popularity, Online Social Networks have become important repositories for information retrieval. The concept of social search, therefore, is gradually being recognized as the next breakthrough in this field, and it is expected to dominate topics in industry. However, retrieving information from OSNs with high Quality of Experience is non-trivial as a result of the prevalence of mobile applications for social networking services. For the sake of shortening user perceived latency Web caching was introduced and has been studied extensively for years. Nevertheless, the previous works seldom focus on the Web caching solutions for social search. In the context of this master’s thesis project, emphasis is given to the design of a Web caching system which is used to cache public data from social media with the objective of improving the user experience in terms of the freshness of data and the perceived service latency. To be more specific, a Web caching strategy named Staleness Bounded LRU algorithm is proposed to limit the term of validity of the cached data. In addition, a Two-Level Web Caching System that adopts the SB-LRU algorithm is proposed in order for shortening the user perceived latency. Results of trace-driven simulations and performance evaluations demonstrate that serving clients with stale data is avoided and the user perceived latencies are significantly shortened when the proposed Web caching system is used in the use case of unauthenticated social search. Besides, the design idea in this project is believed to be helpful to the design of a Web caching system for social search, which is capable of caching user specific data for different clients