Journal of Parallel and Distributed Computing
A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Scheduling with Advanced Reservations
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Making the Grid Predictable through Reservations and Performance Modelling
The Computer Journal
Applying Advance Reservation to Increase Predictability of Workflow Execution on the Grid
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
A provisioning model and its comparison with best-effort for performance-cost optimization in grids
Proceedings of the 16th international symposium on High performance distributed computing
Scheduling Algorithms
Scheduling chain-structured tasks to minimize makespan and mean flow time
Information and Computation
NP-complete scheduling problems
Journal of Computer and System Sciences
Globe'11 Proceedings of the 4th international conference on Data management in grid and peer-to-peer systems
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Advance reservation of resources imporves quality-of-service by assuring the availability of resources at a future time However, it tends to fragment the available resources time and may lead to poor system utilization This paper proposes new job scheduling techniques to address this temporal fragmentation problem The goal is to schedule jobs with dependency to processors whose available times are fragmented into non-continuous time slots We propose a greedy algorithm to find the optimal schedule for jobs with single chain dependency We also propose a dynamic programming algorithm to find the optimal schedule for jobs with multiple-chain dependency In order to reduce scheduling time, we also propose three efficient heuristic algorithms Experimental results indicate that these heuristics are scalable and can find near optimal solutions.