Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Approximation schemes for preemptive weighted flow time
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Improved algorithms for stretch scheduling
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Scheduling Distributed Applications: the SimGrid Simulation Framework
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Online Scheduling to Minimize Average Stretch
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Approximation Algorithms for Average Stretch Scheduling
Journal of Scheduling
Minimizing the stretch when scheduling flows of divisible requests
Journal of Scheduling
Fair, effective, efficient and differentiated scheduling in an enterprise data warehouse
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
A Fair Decentralized Scheduler for Bag-of-Tasks Applications on Desktop Grids
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
A moldable online scheduling algorithm and its application to parallel short sequence mapping
JSSPP'10 Proceedings of the 15th international conference on Job scheduling strategies for parallel processing
A survey of task mapping on production grids
ACM Computing Surveys (CSUR)
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Stretch optimization for virtual screening on multi-user pilot-agent platforms on grid/cloud
Proceedings of the Fourth Symposium on Information and Communication Technology
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In this paper, we consider the problem of scheduling distributed biological sequence comparison applications. This problem lies in the divisible load framework with negligible communication costs. Thus far, very few results have been proposed in this model. We discuss and select relevant metrics for this framework: namely max-stretch and sumstretch. We explain the relationship between our model and the preemptive uni-processor case, and we show how to extend algorithms that have been proposed in the literature for the uni-processor model to the divisible multi-processor problem domain. We recall known results on closely related problems, derive new lower bounds on the competitive ratio of any on-line algorithm, present new competitiveness results for existing algorithms, and develop several new online heuristics. Then, we extensively study the performance of these algorithms and heuristics in realistic scenarios. Our study shows that all previously proposed guaranteed heuristics for max-stretch for the uni-processor model prove to be particularly inefficient in practice. In contrast, we show our on-line algorithms based on linear programming to be nearoptimal solutions for max-stretch. Our study also clearly suggests heuristics that are efficient for both metrics, although a combined optimization is in theory not possible in the general case.