CoT：面向云环境的分散式弹性缓存
CoT: Decentralized Elastic Caches for Cloud Environments
摘要：
分布式缓存被广泛部署，以服务于数十亿用户规模的社交网络和Web应用程序。本文介绍了Cache-on-Track（CoT），这是一种用于云环境的分散，弹性和预测性缓存框架。CoT提出了一种新的缓存替换策略，专门针对服务于倾斜工作负载的小型前端缓存。前端服务器使用重命中跟踪算法来连续跟踪前k个热键。CoT动态缓存跟踪的键中最热的C键。我们的实验表明，CoT的替换策略始终优于命中率的LRU，LFU，和ARC相同的缓存大小上不同的倾斜工作负载。此外，当两个策略配置有相同的跟踪（历史）大小时，\algoname的命中率略高于LRU-2。与其他替换策略相比，CoT实现了服务器大小的负载平衡，前端缓存减少了50%到93.75%。
英文摘要：
Distributed caches are widely deployed to serve social networks and web applications at billion-user scales. This paper presents Cache-on-Track (CoT), a decentralized, elastic, and predictive caching framework for cloud environments. CoT proposes a new cache replacement policy specifically tailored for small front-end caches that serve skewed workloads. Front-end servers use a heavy hitter tracking algorithm to continuously track the top-k hot keys. CoT dynamically caches the hottest C keys out of the tracked keys. Our experiments show that CoT's replacement policy consistently outperforms the hit-rates of LRU, LFU, and ARC for the same cache size on different skewed workloads. Also, \algoname slightly outperforms the hit-rate of LRU-2 when both policies are configured with the same tracking (history) size. CoT achieves server size load-balance with 50\% to 93.75\% less front-end cache in comparison to other replacement policies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
