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
Metrics and Benchmarking for Parallel Job Scheduling
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
The Legion Resource Management System
IPPS/SPDP '99/JSSPP '99 Proceedings of the Job Scheduling Strategies for Parallel Processing
Grid resource management: state of the art and future trends
Grid resource management: state of the art and future trends
An Adaptive Task Scheduling System for Grid Computing
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Model-Driven Simulation of Grid Scheduling Strategies
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
An Expectation Trust Benefit Driven Algorithm for Resource Scheduling in Grid Computing
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
Idle regulation in non-clairvoyant scheduling of parallel jobs
Discrete Applied Mathematics
Workload dynamics on clusters and grids
The Journal of Supercomputing
Load Balancing Oriented Economic Grid Resource Scheduling
PACIIA '08 Proceedings of the 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application - Volume 02
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Computational grid has the potential for solving large-scale scientific problems using distributed resources. Grid scheduling is a vital component of a Computational Grid infrastructure. In this paper, we evaluate our proposed Grid scheduling algorithms (the Multilevel Hybrid Scheduling Algorithm and the Multilevel Dual Queue Scheduling Algorithm) using real workload traces, taken from leading computational centers. An extensive performance comparison is presented using real workload traces to evaluate the efficiency of scheduling algorithms. To facilitate the research, a software tool has been developed which produces a comprehensive simulation of a number of Grid scheduling algorithms. The tool's output is in the form of scheduling performance metrics. The experimental results, based on performance metrics, demonstrate that the performances of our Grid scheduling algorithms give good results. Our proposed scheduling algorithms also support true scalability, that is, they maintain an efficient approach when increasing the number of CPUs or nodes. This paper also includes a statistical analysis of workload traces to present the nature and behavior of jobs.