TY - GEN
T1 - Elastic Consistent Hashing for Distributed Storage Systems
AU - Xie, Wei
AU - Chen, Yong
N1 - Funding Information:
This research is supported in part by the National Science Foundation under grant CNS-1162488, CNS-1338078, and CCF-1409946.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/30
Y1 - 2017/6/30
N2 - Elastic distributed storage systems have been increasingly studied in recent years because power consumption has become a major problem in data centers. Much progress has been made in improving the agility of resizing small-A nd large-scale distributed storage systems. However, most of these studies focus on metadata based distributed storage systems. On the other hand, emerging consistent hashing based distributed storage systems are considered to allow better scalability and are highly attractive. We identify challenges in achieving elasticity in consistent hashing based distributed storage. These challenges cannot be easily solved by techniques used in current studies. In this paper, we propose an elastic consistent hashing based distributed storage to solve two problems. First, in order to allow a distributed storage to resize quickly, we modify the data placement algorithm using a primary server design and achieve an equal-work data layout. Second, we propose a selective data re-integration technique to reduce the performance impact when resizing a cluster. Our experimental and trace analysis results confirm that our proposed elastic consistent hashing works effectively and allows significantly better elasticity.
AB - Elastic distributed storage systems have been increasingly studied in recent years because power consumption has become a major problem in data centers. Much progress has been made in improving the agility of resizing small-A nd large-scale distributed storage systems. However, most of these studies focus on metadata based distributed storage systems. On the other hand, emerging consistent hashing based distributed storage systems are considered to allow better scalability and are highly attractive. We identify challenges in achieving elasticity in consistent hashing based distributed storage. These challenges cannot be easily solved by techniques used in current studies. In this paper, we propose an elastic consistent hashing based distributed storage to solve two problems. First, in order to allow a distributed storage to resize quickly, we modify the data placement algorithm using a primary server design and achieve an equal-work data layout. Second, we propose a selective data re-integration technique to reduce the performance impact when resizing a cluster. Our experimental and trace analysis results confirm that our proposed elastic consistent hashing works effectively and allows significantly better elasticity.
UR - http://www.scopus.com/inward/record.url?scp=85027681096&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2017.88
DO - 10.1109/IPDPS.2017.88
M3 - Conference contribution
AN - SCOPUS:85027681096
T3 - Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017
SP - 876
EP - 885
BT - Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 31st IEEE International Parallel and Distributed Processing Symposium, IPDPS 2017
Y2 - 29 May 2017 through 2 June 2017
ER -