TY - GEN
T1 - R-Memcached
T2 - 1st International Conference on Big Data Computing and Communications, BigCom 2015
AU - Liu, Chengjian
AU - Ouyang, Kai
AU - CHU, Xiaowen
AU - LIU, Hai
AU - LEUNG, Yiu Wing
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 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, and evaluation of R-Memcached, a reliable in-memory key-value cache system that is built on top of the popular Memcached. 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.
AB - 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, and evaluation of R-Memcached, a reliable in-memory key-value cache system that is built on top of the popular Memcached. 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.
UR - http://www.scopus.com/inward/record.url?scp=84947230272&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-22047-5_20
DO - 10.1007/978-3-319-22047-5_20
M3 - Conference proceeding
AN - SCOPUS:84947230272
SN - 9783319220468
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 256
BT - Big Data Computing and Communications - 1st International Conference, BigCom 2015, Proceedings
A2 - Argamon, Shlomo
A2 - Li, Xiang Yang
A2 - Xiong, Hui
A2 - Li, JianZhong
A2 - Wang, Yu
PB - Springer Verlag
Y2 - 1 August 2015 through 3 August 2015
ER -