Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A worldwide flock of Condors: load sharing among workstation clusters
Future Generation Computer Systems - Special issue: resource management in distributed systems
What are fuzzy rules and how to use them
Fuzzy Sets and Systems - Special issue dedicated to the memory of Professor Arnold Kaufmann
QoS routing in networks with uncertain parameters
IEEE/ACM Transactions on Networking (TON)
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Legion: The Next Logical Step Toward a Nationwide Virtual Computer
Legion: The Next Logical Step Toward a Nationwide Virtual Computer
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
G-FRoM: Grid Resources Pricing A Fuzzy Real Option Model
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
Using fuzzy control to maximize profits in service level management
IBM Systems Journal
Admission control for statistical QoS: theory and practice
IEEE Network: The Magazine of Global Internetworking
A grid resources valuation model using fuzzy real option
ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
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A computational grid ensures the on-demand delivery of computing resources, in a security-aware, shared, scalable, and standardsbased computing environment. A major concern is how to evolve a general and an encompassing framework that guarantees users' satisfaction for using grid computing resources measured as Quality of Services (QoS). To obtain a higher QoS, effective QoS perceived by subscribers (users) must conform to specified QoS agreements in the Service Level Agreements (SLAs) document - a legal contract between the Grid Services Provider (GSP) and users. Sometimes, the effective user QoS does not conform to the specifications in the SLA because of the vagueness in linguistic definitions in the SLA. Existing approaches overcommitted grid resources to satisfy QoS requirement in SLA. In this paper, we propose a fuzzy logic framework for calibrating a user QoS that addresses the vagueness in linguistic definitions of the SLA document without overcommitting grid resources.