An efficient cache management algorithm for streaming workloads

Kyungwoon Cho, Hyokyung Bahn

Research output: Contribution to journalArticlepeer-review


In this paper, we present a novel cache management algorithm for real-world streaming workloads. Streaming workloads are believed to exhibit very large and sequential access patterns, which has been the main consideration in designing media caching algorithms. However, legacy caching algorithms do not fully utilise fine-grained access patterns of streaming workloads and also tend to ignore human interactivity. In this paper, we present the least expectation first (LEF) algorithm, which manages a large number of block caches as two-level grouping. Specifically, we select caching and eviction targets based on the expected gain of the cached data blocks, thereby improving the cache hit ratio significantly. Experimental results show that the proposed algorithm performs better than well-known interval caching and LRU algorithms with respect to the hit ratio and the I/O bandwidth.

Original languageEnglish
Pages (from-to)402-414
Number of pages13
JournalInternational Journal of Networking and Virtual Organisations
Issue number4
StatePublished - 2020

Bibliographical note

Funding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korea government (MSIT) (No. 2016R1A2B4015750) and (MOE) (2016R1A6A3A11930295).

Publisher Copyright:
Copyright © 2020 Inderscience Enterprises Ltd.


  • Buffer caching
  • Cache hit ratio
  • Caching algorithm
  • I/O bandwidth
  • Interval caching
  • LRU algorithm
  • Sequential access
  • Streaming workload


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