Paper Info
Title
Improving data availability for a cluster file system through replication
Abstract
Data availability is a challenging issue for large- scale cluster file systems built upon thousands of individual storage devices. Replication is a well-known solution used to improve data availability. However, how to efficiently guarantee replicas consistency under concurrent conflict mutations remains a challenge. Moreover, how to quickly recover replica consistency from a storage server crash or storage device failure is also a tough problem. In this paper, we present a replication-based data availability mechanism designed for a large-scale cluster file system prototype named LionFS. Unlike other replicated storage systems that serialize replica updates, LionFS introduces a relaxed consistency model to enable concurrent updating all replicas for a mutation operation, greatly reducing the latency of operations. LionFS ensures replica consistency if applications use file locks to synchronize the concurrent conflict mutations. Another novelty of this mechanism is its light-weight log, which only records failed mutations and imposes no overhead on failure-free execution and low overhead when some storage devices are unavailable. Furthermore, recovery of replica consistency needs not stop the file system services and running applications. Performance evaluation shows that our solution achieves 50-70% higher write performance than serial replica updates. The logging overhead is shown to be low, and the recovery time is proportional to the amount of data written during the failure.
Year
DOI
Venue
2008
10.1109/IPDPS.2008.4536154
IPDPS
Keywords
Field
DocType
concurrent conflict mutations,relaxed consistency model,failure free execution,large scale cluster file system,replication,very large databases,data availability improvement,replicated databases,lionfs,bandwidth,computer architecture,storage system,availability,mechanism design
Replica,File server,File system,Synchronization,Serialization,Latency (engineering),Computer science,Parallel computing,Computer network,Bandwidth (signal processing),Consistency model,Distributed computing
Conference
ISSN
ISBN
Citations 
1530-2075 E-ISBN : 978-1-4244-1694-3
978-1-4244-1694-3
2
PageRank 
References 
Authors
0.43
16
4
Name
Order
Citations
PageRank
Jin Xiong115715.95
Jianyu Li220.43
Rongfeng Tang3233.35
Yiming Hu463944.91