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The CLOCK Data-Aware Eviction Approach

The CLOCK Data-Aware Eviction Approach

This video was recorded at 11th Extended Semantic Web Conference (ESWC), Crete 2014. Processing streams rather than static les of Linked Data has gained increasing importance in the web of data. When processing data-streams system builders are faced with the conundrum of guaranteeing a constant maximum response time with limited resources and, possibly, no prior information on the data arrival frequency. One approach to address this issue is to delete data from a cache during processing { a process we call eviction. The goal of this paper is to show that data-driven eviction outperforms today's dominant data-agnostic approaches such as rst-in-rst-out or random deletion. Specically, we rst introduce a method called Clock that evicts data from a join cache based on the likelihood estimate of contributing to a join in the future. Second, using the well-established SR-Bench bench-mark as well as a data set from the IPTV domain, we show that Clock out-performs data-agnostic approaches indicating its usefulness for resource-limited linked data stream processing.


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