Scheduling Algorithms
Scheduling Distributed Applications: the SimGrid Simulation Framework
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Overview of a Performance Evaluation System for Global Computing Scheduling Algorithms
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
QoS guided min-min heuristic for grid task scheduling
Journal of Computer Science and Technology - Grid computing
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Concurrency and Computation: Practice & Experience
Software—Practice & Experience
Parallel machine scheduling through column generation: minimax objective functions
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
A job scheduling framework for large computing farms
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
WSEAS Transactions on Systems and Control
Alea 2: job scheduling simulator
Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
Optimal job packing, a backfill scheduling optimization for a cluster of workstations
The Journal of Supercomputing
Knowledge acquisition in fuzzy-rule-based systems with particle-swarm optimization
IEEE Transactions on Fuzzy Systems
Improving expert meta-schedulers for grid computing through weighted rules evolution
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
International Journal of Approximate Reasoning
Fuzzy scheduling with swarm intelligence-based knowledge acquisition for grid computing
Engineering Applications of Artificial Intelligence
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This work concentrates on the design of a system intended for study of advanced scheduling techniques for planning various types of jobs in a Grid environment. The solution is able to deal with common problems of the job scheduling in Grids like heterogeneity of jobs and resources, and dynamic runtime changes such as arrivals of new jobs. Our new simulator called Alea is based on the GridSim simulation toolkit which we extended to provide a simulation environment that supports simulation of varying Grid scheduling problems. To demonstrate the features of the GridSim environment, we implemented an experimental centralised Grid scheduler which uses advanced scheduling techniques for schedule generation. By now local search based algorithms and some dispatching rules were tested. The scheduler is capable to handle both static and dynamic situation. In the static case, all jobs are known in advance while the dynamic situation means that jobs appear in the system during simulation. In this case generated schedule is changing through time as some jobs are already finished while the new ones are arriving. Comparison of FCFS, local search and dispatching rules is presented for both cases and we demonstrate that the new local search based algorithm provides the best schedule while keeping the running time acceptable.