Paper Info
Title
Enhanced Self-Coding for Available Memcached
Abstract
Erasure coding is a novel approach used in key/value(KV) cache systems for high data availability in memory and is often applied across multiple KV objects. Self-coding, which performs coding on the splits of each individual KV object, has been newly employed for KV caching. However, for Memcached which is one of the most popular KV cache systems, its fixedsize allocation mechanism fails to adapt random sizes of splits of different KV objects; in addition, its consistent hashing infrastructure may incur substantial data traffic due to split redistribution in case of scaling (e.g. adding a new cache server). In this paper, we address these issues by proposing an efficient self-coding framework (ESCO) for memory overhead reduction and better scaling performance. ESCO employs adaptive splitting of individual KV objects to reduce memory overhead, and also designs hybrid distribution of splits for fast data scaling. We implement and deploy ESCO atop Memcached. Evaluations show that the memory space can be saved by up to 23.2% and the scaling performance can be improved by up to 15X over the state-of-the-arts.
Year
DOI
Venue
2018
10.1109/BDCloud.2018.00106
2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom)
Keywords
Field
DocType
Erasure Coding,Memcached,In memory Key/Value Store,Memory Management,Consistent Hashing
Data traffic,Data availability,Cache,Computer science,Coding (social sciences),Memory management,Consistent hashing,Scaling,Multimedia,Erasure code,Distributed computing
Conference
ISSN
ISBN
Citations 
2158-9178
978-1-7281-1141-4
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Liangfeng Cheng121.72
Yuchong Hu232227.44
Wei Wei394.21
Renzhi Xiao411.71