An efficient cache management algorithm for streaming workloads. (4th April 2020)

• Record Type: Journal Article
• Authors: Cho, Kyungwoon; Bahn, Hyokyung
• Is Part Of: International journal of networking and virtual organisations. Volume 22:Number 4(2020)
• Page Start: 402
• Page End: 414
• Publication Date: 2020-04-04
• Subjects: caching algorithm -- interval caching -- LRU algorithm -- streaming workload -- sequential access -- buffer caching -- I/O bandwidth -- cache hit ratio; Computer networks -- Periodicals; Information networks -- Periodicals; Virtual corporations -- Periodicals; Electronic commerce -- Periodicals; Management information systems -- Periodicals; Management -- Data processing -- Periodicals; 004.65
• Languages: English
• ISSNs: 1470-9503

Abstract

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.