Paper Info
Title
Jump-start cloud: efficient deployment framework for large-scale cloud applications
Abstract
Reducing the time that a user has to occupy resources for completing cloud tasks can improve cloud efficiency and lower user cost. Such a time, called cloud time, consists of cloud deployment time and application running time. In this work we design jump-start cloud, under which an efficient cloud deployment scheme is proposed for minimizing cloud time. In particular, VM cloning based on disk image sharing has been implemented for fast VM and application deployment. For applications with heavy disk visits, the post-deployment quality of service (QoS) may suffer from image sharing and consequently, application running time will increase. To solve this problem, different image distribution schemes have been designed. We test jump-start cloud through a Hadoop based benchmark and MapReduce applications. Experiment studies show that our design saves application installation time and meanwhile, keeps application running time reasonably low, thus makes cloud time shorter.
Year
DOI
Venue
2012
10.1002/cpe.1847
Concurrency and Computation: Practice and Experience
Keywords
Field
DocType
mapreduce application,jump-start cloud,large-scale cloud application,application installation time,efficient cloud deployment scheme,significant cloud resource,cloud task,efficient deployment framework,cloud efficiency,cloud time,cloud deployment time,application deployment,different image distribution scheme,quality of service,time consistency
Software deployment,Virtual machine,Computer science,Jump start,Cloud deployment,Quality of service,Real-time computing,Image sharing,Cloud testing,Distributed computing,Cloud computing
Journal
Volume
Issue
ISSN
24
17
1532-0626
Citations 
PageRank 
References 
10
1.16
12
Authors
4
Name
Order
Citations
PageRank
Xiaoxin Wu147538.35
Zhiming Shen248216.67
Ryan Wu3272.34
Yunfeng Lin442223.23