Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Dynamic mapping of a class of independent tasks onto heterogeneous computing systems
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
The AppLeS parameter sweep template: user-level middleware for the grid
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
A Peer-to-Peer Approach to Resource Location in Grid Environments
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
SRDS '98 Proceedings of the The 17th IEEE Symposium on Reliable Distributed Systems
An experimental study of online scheduling algorithms
Journal of Experimental Algorithmics (JEA)
A Comparison among Grid Scheduling Algorithms for Independent Coarse-Grained Tasks
SAINT-W '04 Proceedings of the 2004 Symposium on Applications and the Internet-Workshops (SAINT 2004 Workshops)
Performance evaluation of market-based resource allocation for Grid computing: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
Operating System Concepts
Job demand models for optical grid research
ONDM'07 Proceedings of the 11th international IFIP TC6 conference on Optical network design and modeling
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Grid computing has emerged as a new paradigm for distributed systems, which promotes sharing of distributed resources. To maximize its benefits, it is essential to discover the resources available on the grid, and then effectively map the jobs to the resources for maximizing a given objective function. This paper focuses on the problem of matching of jobs to resources in a computing grid. Jobs are classified based on their service demands. Matching policies that use only the knowledge of job classes are introduced in this paper; simulation experiments demonstrate the effectiveness of these policies. Under a variety of different workload parameters the proposed matching policies demonstrate a performance comparable to, or better than, the well-known Minimum Completion Time matching policy, which is based on detailed a priori knowledge of jobs and resource characteristics.