论文标题
COT：云环境的分散弹性缓存
CoT: Decentralized Elastic Caches for Cloud Environments
论文作者
论文摘要
分布式缓存被广泛部署，以在十亿用户量表上为社交网络和Web应用程序提供服务。本文介绍了Cache-on-track（COT），这是云环境的分散，弹性和预测的缓存框架。 COT提出了一种新的缓存替换策略，专门针对用于偏斜工作量的小型前端缓存。前端服务器使用重型击球手跟踪算法来连续跟踪顶级热键。 COT动态缓存最热的C键从轨道键中。我们的实验表明，COT的替换策略始终优于LRU，LFU和ARC的命中率，在不同的偏斜工作量上具有相同的高速缓存大小。另外，当两个策略配置具有相同的跟踪（历史记录）大小时，\ algoname略优于LRU-2的命中率。与其他替换策略相比，COT以50 \％至93.75 \％的前端缓存实现服务器尺寸负载平衡。
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.
