Title
Resource Access Management for a Utility Hosting Enterprise Applications
Abstract
In this paper we introduce a Resource Access Management (RAM) framework for resource utilities that facilitates Class of Service (CoS) based automated resource management. The framework may be used to offer resources on demand to enterprise applications that have time varying resource needs. The classes of service include guaranteed, predictable best effort, and best effort. The analytical apparatus we exploit requires the notion of application demand profiles that specify each application's resource requirements. These profiles may be statistical in nature. Consequently a policing mechanism is introduced to constrain each application's resource usage within its profile. A case study that exploits data from 48 data center servers, is used to demonstrate the framework. We show that our techniques are effective in: exploiting statistical multiplexing while providing service level assurances, limiting application demands in the presence of hostile application behaviour, and providing for differentiated service levels as planned.
Year
DOI
Venue
2003
10.1109/INM.2003.1194210
Integrated Network Management
Keywords
Field
DocType
business communication,multiplexing,quality of service,statistical analysis,telecommunication network management,CoS based automated resource management,admission control,application demand profiles,application resource usage,best effort service,class of service,credit-based policing mechanism,data center servers,differentiated service levels,enterprise applications,guaranteed service,hostile application behaviour,policing mechanism,predictable best effort service,resource access management,resource utilities,service level assurances,statistical multiplexing,statistical profiles,utility computing
Resource management,Access management,Service level,Computer science,Computer network,Quality of service,Human resource management system,Differentiated service,Utility computing,Class of service,Distributed computing
Conference
Volume
ISSN
Citations 
118
1571-5736
5
PageRank 
References 
Authors
1.15
6
3
Name
Order
Citations
PageRank
Jerry Rolia164147.35
Zhu, X.251.15
M. Arlitt333032.79