Visible to the public Demand-driven Cache Allocation Based on Context-aware Collaborative Filtering

TitleDemand-driven Cache Allocation Based on Context-aware Collaborative Filtering
Publication TypeConference Paper
Year of Publication2018
AuthorsChen, Muhao, Zhao, Qi, Du, Pengyuan, Zaniolo, Carlo, Gerla, Mario
Conference NameProceedings of the Eighteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5770-8
Keywordscache allocation, collaborative filtering, Demand-driven caching, Metrics, pubcrawl, Resiliency, Scalability, Web Caching
AbstractMany recent advances of network caching focus on i) more effectively modeling the preferences of a regional user group to different web contents, and ii) reducing the cost of content delivery by storing the most popular contents in regional caches. However, the context under which the users interact with the network system usually causes tremendous variations in a user group's preferences on the contents. To effectively leverage such contextual information for more efficient network caching, we propose a novel mechanism to incorporate context-aware collaborative filtering into demand-driven caching. By differentiating the characterization of user interests based on a priori contexts, our approach seeks to enhance the cache performance with a more dynamic and fine-grained cache allocation process. In particular, our approach is general and adapts to various types of context information. Our evaluation shows that this new approach significantly outperforms previous non-demand-driven caching strategies by offering much higher cached content rate, especially when utilizing the contextual information.
URLhttp://doi.acm.org/10.1145/3209582.3225198
DOI10.1145/3209582.3225198
Citation Keychen_demand-driven_2018