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Mei Li, Hong-Jun Zhang, Yan-Jun Wu, Chen Zhao. MemSC: A Scan-Resistant and Compact Cache Replacement Framework for Memory-Based Key-Value Cache Systems[J]. Journal of Computer Science and Technology, 2017, 32(1): 55-67. DOI: 10.1007/s11390-017-1705-3
Citation: Mei Li, Hong-Jun Zhang, Yan-Jun Wu, Chen Zhao. MemSC: A Scan-Resistant and Compact Cache Replacement Framework for Memory-Based Key-Value Cache Systems[J]. Journal of Computer Science and Technology, 2017, 32(1): 55-67. DOI: 10.1007/s11390-017-1705-3

MemSC: A Scan-Resistant and Compact Cache Replacement Framework for Memory-Based Key-Value Cache Systems

  • Memory-based key-value cache systems, such as Memcached and Redis, have become indispensable components of data center infrastructures and have been used to cache performance-critical data to avoid expensive back-end database accesses. As the memory is usually not large enough to hold all the items, cache replacement must be performed to evict some cached items to make room for the newly coming items when there is no free space. Many real-world workloads target small items and have frequent bursts of scans (a scan is a sequence of one-time access requests). The commonly used LRU policy does not work well under such workloads since LRU needs a large amount of metadata and tends to discard hot items with scans. Small decreases in hit ratio can result in large end-to-end losses in these systems. This paper presents MemSC, which is a scan-resistant and compact cache replacement framework for Memcached. MemSC assigns a multi-granularity reference flag for each item, which requires only a few bits (two bits are enough for general use) per item to support scanresistant cache replacement policies. To evaluate MemSC, we implement three representative cache replacement policies (MemSC-HM, MemSC-LH, and MemSC-LF) on MemSC and test them using various workloads. The experimental results show that MemSC outperforms prior techniques. Compared with the optimized LRU policy in Memcached, MemSC-LH reduces the cache miss ratio and the memory usage of the resulting system by up to 23% and 14% respectively.
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