@article{Liu2015, 
author = {Chengjian Liu and Kai Ouyang and Xiaowen Chu and Hai Liu and Yui-Wing Leung},
title = {R-Memcached: A Reliable In-Memory Cache for Big Key-Value Stores},
year = {2015},
journal = {Tsinghua Science and Technology},
volume = {20},
number = {6},
pages = {560-573},
keywords = {in-memory cache, fault tolerance, key-value store},
url = {https://www.sciopen.com/article/10.1109/TST.2015.7349928},
doi = {10.1109/TST.2015.7349928},
abstract = {Large-scale key-value stores are widely used in many Web-based systems to store huge amount of data as (key, value) pairs. In order to reduce the latency of accessing such (key, value) pairs, an in-memory cache system is usually deployed between the front-end Web system and the back-end database system. In practice, a cache system may consist of a number of server nodes, and fault tolerance is a critical feature to maintain the latency Service-Level Agreements (SLAs). In this paper, we present the design, implementation, analysis, and evaluation of R-Memcached, a reliable in-memory key-value cache system that is built on top of the popular Memcached software. R-Memcached exploits coding techniques to achieve reliability, and can tolerate up to two node failures. Our experimental results show that R-Memcached can maintain very good latency and throughput performance even during the period of node failures.}
}