Abstract
Many applications in federated Grids have quality-of-service (QoS) constraints such as deadline. Admission control mechanisms assure QoS constraints of the applications by limiting the number of user requests accepted by a resource provider. However, in order to maximize their profit, resource owners are interested in accepting as many requests as possible. In these circumstances, the question that arises is: what is the effective number of requests that can be accepted by a resource provider in a way that the number of accepted external requests is maximized and, at the same time, QoS violations are minimized. In this paper, we answer this question in the context of a virtualized federated Grid environment, where each Grid serves requests from external users along with its local users and requests of local users have preemptive priority over external requests. We apply analytical queuing model to address this question. Additionally, we derive a preemption-aware admission control policy based on the proposed model. Simulation results under realistic working conditions indicate that the proposed policy improves the number of completed external requests (up to 25%). In terms of QoS violations, the 95% confidence interval of the average difference with other policies is between (14.79%,18.56%).
Original language | English |
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Title of host publication | 26th IEEE International Conference on Advanced Information Networking and Applications : Fukuoka Institute of Technology, Fukuoka, Japan, 26-29 March 2012 |
Publisher | IEEE |
Pages | 854-861 |
Number of pages | 8 |
ISBN (Print) | 9780769546513 |
DOIs | |
Publication status | Published - 2012 |
Event | International Conference on Advanced Information Networking and Applications - Duration: 26 Mar 2012 → … |
Conference
Conference | International Conference on Advanced Information Networking and Applications |
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Period | 26/03/12 → … |
Keywords
- computational grids (computer systems)
- computer simulation
- quality of service
- queuing theory
- resource provisioning
- virtual machines