Multi-Version Coding-An Information-Theoretic Perspective of Consistent Distributed Storage

被引:8
作者
Wang, Zhiying [1 ]
Cadambe, Viveck R. [2 ]
机构
[1] Univ Calif Irvine, Ctr Pervas Commun & Comp, Irvine, CA 92697 USA
[2] Penn State Univ, Dept Elect Engn, State Coll, PA 16802 USA
关键词
Consistency; distributed storage; distributed computing; erasure coding; index coding; shared memory;
D O I
10.1109/TIT.2017.2725273
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In applications of distributed storage systems to distributed computing and implementation of key-value stores, the following property, usually referred to as consistency in distributed computing, is an important requirement: as the data stored changes, the latest version of the data must be accessible to a client that connects to the storage system. Motivated by technological trends where key-value stores are increasingly implemented in high-speed memory, an information theoretic formulation called multi-version coding is introduced in this paper in order to understand and minimize the memory overhead of consistent distributed storage. Multi-version coding is characterized by nu totally ordered versions of a message and a storage system with n servers. At each server, values corresponding to an arbitrary subset of the nu versions are received and encoded. For any subset of c servers in the storage system, the value corresponding to the latest common version or a later version, as per the total ordering, among the c servers is required to be decodable. An achievable multi-version code construction via linear coding and a converse result that shows that the construction is asymptotically tight when nu|(c-1) are provided. An implication of the converse is that there is an inevitable price, in terms of storage cost, to ensure consistency in distributed storage systems.
引用
收藏
页码:4540 / 4561
页数:22
相关论文
共 49 条
[1]  
Abd-El-Malek Michael, 2005, Operating Systems Review (OSR), V39, P59, DOI [10.1145/1095810.1095817, DOI 10.1145/1095810.1095817]
[2]   Using erasure codes efficiently for storage in a distributed system [J].
Aguilera, MK ;
Janakiraman, R ;
Xu, LH .
2005 INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS, PROCEEDINGS, 2005, :336-345
[3]  
Ali Ramy E., 2016, 2016 IEEE Information Theory Workshop (ITW), P176, DOI 10.1109/ITW.2016.7606819
[4]  
[Anonymous], 2010, CouchDB: The Definitive Guide: Time to Relax
[5]  
[Anonymous], 1996, Distributed algorithms
[6]  
[Anonymous], 1987, PODC
[7]  
[Anonymous], 2007, STREAM CONTROL TRANS
[8]   SHARING MEMORY ROBUSTLY IN MESSAGE-PASSING SYSTEMS [J].
ATTIYA, H ;
BARNOY, A ;
DOLEV, D .
JOURNAL OF THE ASSOCIATION FOR COMPUTING MACHINERY, 1995, 42 (01) :124-142
[9]   Fault tolerance in distributed systems using fused state machines [J].
Balasubramanian, Bharath ;
Garg, Vijay K. .
DISTRIBUTED COMPUTING, 2014, 27 (04) :287-311
[10]  
Brahma S., 2012, Proceedings of the 2012 IEEE International Symposium on Information Theory - ISIT, P2251, DOI 10.1109/ISIT.2012.6283912