Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Autopilot: Adaptive Control of Distributed Applications
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
An approach for quality of service adaptation in service-oriented Grids: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Online resource matching for heterogeneous grid environments
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Grid capacity planning with negotiation-based advance reservation for optimized QoS
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Negotiation Model Supporting Co-Allocation for Grid Scheduling
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Cooperative service level agreement
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Formal QoS Policy Based Grid Resource Provisioning Framework
Journal of Grid Computing
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Applications using Grid computing infrastructure usually require resources allocation to satisfy their Quality of Service (QoS) requirements. Given that the Grid infrastructure is a set of computing resources geographically distributed, the support of Grid applications requires the allocation of computing resources and bandwidth to enable communication among these resources. The objective is to accommodate as many applications as possible while still satisfying their requirements. Ideally, we would like to accommodate a given Grid application using a set of computing resources (e.g., one server) that are not geographically distributed (e.g., in the same LAN); however, this is not always possible. Indeed, to increase the probability of accommodating Grid applications, we may need to use computing resources scattered all over the network; in this case, bandwidth allocation is required to enable communication among these resources. In this paper, we propose an optimization model that enables the "simultaneous" allocation of computing resources and bandwidth for Grid application while maximizing the number of Grid applications being accommodated. A heuristic is proposed to solve the model with an acceptable response time; simulations show that the proposed approach outperforms existing classical approaches.