DocumentCode
1689427
Title
Using Self-Announcer Approach for Resource Availability Detection in Grid Environment
Author
Bouyer, Asgarali ; Mohebi, Ehsan ; Abdullah, A.H.
Author_Institution
Miyandoab Branch, Islamic Azad Univ., Miyandoad, Iran
fYear
2009
Firstpage
151
Lastpage
156
Abstract
Since the Grid is a dynamic environment, the detection of available resources and prediction of resource availability in near future is important for resource scheduling. In a Grid environment, prediction and evaluation of resource availability is the prerequisite for a reasonable resource selection and good scheduling guarantee. There are many approaches for discovery and prediction of the resource availability that have some weaknesses (e.g., complexity time, predicting, using out of date data, etc). In this paper, we present a new method for detection of available resource based on online-announcer with no inquiry from Grid scheduler. We use a rough set analysis in each grid node to get some useful rules for predicting about nodepsilas behavior in the grid. The experiment results show that our proposed approach is fast algorithm and it applies effectively a reliable method to predict of proper resources for scheduling.
Keywords
grid computing; resource allocation; scheduling; available resource; dynamic environment; grid environment; grid evaluation; grid prediction; grid scheduler; online announcer; resource availability detection; resource scheduling; resource selection; rough set analysis; scheduling guarantee; self-announcer approach; Availability; Computer science; Computerized monitoring; Databases; Finishing; Geographic Information Systems; Grid computing; Information systems; Information technology; Processor scheduling; Rough set; availability; resource scheduling; scheduler;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing in the Global Information Technology, 2009. ICCGI '09. Fourth International Multi-Conference on
Conference_Location
Cannes, La Bocca
Print_ISBN
978-1-4244-4680-3
Electronic_ISBN
978-0-7695-3751-1
Type
conf
DOI
10.1109/ICCGI.2009.30
Filename
5279846
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