Paper Info
Title
A resource management framework for multi-tier service delivery in autonomic virtualized environments.
Abstract
Large data centers usually host many different services on a shared computing infrastructure, for which on-demand resource management is necessary to maximize providers' revenues by meeting service quality targets at least operational cost. This paper presents a novel architecture of autonomic resource management framework based on virtualized Service-Oriented Computing (SOC) environment. A non-linear continuous optimization problem is defined for adaptive resource allocation and a model-based approach is adopted to solve this problem. Different from traditional approaches, the analytic model we established provides probabilistic performance guarantees and considers non-steady-state behavior assisted by admission control. Results of prototype experiments demonstrate that the performance of multiple services has been greatly improved by taking advantage of fine-grained resource sharing, while incurring much lower resource usage cost Also, differentiated service qualifies could be provided to different client classes through our dynamic resource allocation scheme.
Year
DOI
Venue
2008
10.1109/NOMS.2008.4575149
NOMS
Keywords
Field
DocType
local area networks,steady state,service delivery,service oriented computing,autonomic computing,java,web server,virtual environment,resource allocation,quality of service,resource sharing,service quality,resource management,resource manager,continuous optimization,differentiated service
Resource management,Autonomic computing,Service quality,Computer science,Quality of service,Computer network,Human resource management system,Differentiated service,Resource allocation,Shared resource,Distributed computing
Conference
Volume
Issue
ISSN
null
null
null
ISBN
Citations 
PageRank 
978-1-4244-2066-7
14
1.31
References 
Authors
15
5
Name
Order
Citations
PageRank
Xiaoying Wang111513.21
Dongjun Lan21099.64
Xing Fang328326.18
Ye, M.4473.10
Ying Chen536134.10