Resource-constrained project scheduling: a survey of recent developments
Computers and Operations Research
Resource discovery in distributed networks
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
Parallel Job Scheduling: Issues and Approaches
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
Design and Evaluation of a Resource Selection Framework for Grid Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Scheduling Co-Reservations with Priorities in Grid Computing Systems
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
QoS guided min-min heuristic for grid task scheduling
Journal of Computer Science and Technology - Grid computing
Stochastic evaluation of fair scheduling with applications to quality-of-service in broadband wireless access networks
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Enhancing the effective utilisation of grid clusters by exploiting on-line performability analysis
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
A Broker-Based Approach to Resource Discovery and Selection in Grid Environments
ICCEE '08 Proceedings of the 2008 International Conference on Computer and Electrical Engineering
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Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and a job-scheduling algorithm. The architecture is scalable and does not assume control of local site resources. In our algorithm Grid Resource Manager or Grid Scheduler performs resource brokering and job scheduling. The scheduler selects computational resources based on job requirements, job characteristics and information provided by the resources. The main aim of these schedulers is to minimize the total time to release for the individual application. The Time To Release (TTR) includes the processing time of the program, waiting time in the queue, transfer of input and output data to and from the resource. Since grid resources are heterogeneous and distributed over many areas the transmission time is very important criteria. In this paper,an algorithm for minimum time to release is proposed. The proposed scheduling algorithm has been compared with other scheduling schemes such as First Come First Served (FCFS) and Min-Min. These existing algorithms does not consider the transmission time (in time and out time) when scheduling jobs to resources. The proposed algorithm has been verified through the GridSim simulation toolkit and the simulation results confirm that the proposed algorithm produce schedules where the execution time of the application is minimized. The average weighted response times of all submitted jobs decrease up to about 19.79%. The results have been verified using different workloads and Grid configurations.