In this work, we explore a score-based approach to manage a cache system. With the proposed method, the cache can better discriminate the input requests and improve the overall performances. We created a score based discriminator using the file statistics. The score represents the weight of a file. We tested several functions to compute the file weight used to determine whether a file has to be stored in the cache or not. We developed a solution experimenting on a real cache manager named XCache, that is used within the Compact Muon Solenoid (CMS) data analysis workflow. The aim of this work is optimizing to reduce maintaining costs of the cache system without compromising the user experience.
CITATION STYLE
Tracolli, M., Baioletti, M., Ciangottini, D., Poggioni, V., & Spiga, D. (2020). An Intelligent Cache Management for Data Analysis at CMS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12250 LNCS, pp. 320–332). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58802-1_24
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