Web services on demand: WSLA-driven automated management
IBM Systems Journal
Statistical service assurances for applications in utility grid environments
Performance Evaluation - Special issue: Distributed systems performance
Decentralised application placement
Future Generation Computer Systems - Special issue: Advanced grid technologies
The Journal of Supercomputing
No "power" struggles: coordinated multi-level power management for the data center
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Modeling remote desktop systems in utility environment with application to QoS management
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
An efficient overload control strategy in cloud
APWeb'12 Proceedings of the 14th international conference on Web Technologies and Applications
P2EST: parallelization philosophies for evaluating spatio-temporal queries
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
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In this paper we focus on techniques to support admissioncontrol and advance resource reservation for applicationsacquiring information technology (IT) resources fromutility grid environments. Utility grid environments offerprogrammatic access to resources for complex multitierapplications. In particular we consider business applicationswhich require resources continuously but that haveresource demands that change regularly based on factorssuch as time of day and day of week. We present a statisticaldemand profile approach for characterizing time varyingapplication resource requirements along with a methodthat provides statistical assurances regarding the numberof resources needed to satisfy the combined requirementsof many applications over time. We illustrate the feasibilityof our approach with a case study that uses resourceutilization information from 48 data center servers. Simulationexperiments explore the sensitivity of the assurancesto correlations between application resource demands andthe precision of the demand profiles.