Messages Scheduling for Data Redistribution between Clusters
Identifieur interne : 006B71 ( Main/Curation ); précédent : 006B70; suivant : 006B72Messages Scheduling for Data Redistribution between Clusters
Auteurs : Johanne Cohen [France] ; Emmanuel Jeannot [France] ; Nicolas Padoy [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
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Abstract
Abstract: In this paper we study the general problem of parallel data redistribution over a network. Given a set of communications between two parallel machines interconnected by a backbone, we wish to minimize the total time required for the completion of all communications assuming that communications can be preempted and that preemption comes with an extra cost. Our problem, called k-Preemptive bipartite scheduling (KPBS) is proven to be NP-Complete. Moreover we prove that approximating KPBS problem within a ratio number smaller that $\frac{4}{3}$ is impossible unless P=NP. In spite of this negative result, we study a lower bound on the cost of KPBS problem in terms of its parameters, and we propose an approximation algorithm with ratio 2 and fast heuristics.
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DOI: 10.1007/978-3-540-24669-5_116
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<front><div type="abstract" xml:lang="en">Abstract: In this paper we study the general problem of parallel data redistribution over a network. Given a set of communications between two parallel machines interconnected by a backbone, we wish to minimize the total time required for the completion of all communications assuming that communications can be preempted and that preemption comes with an extra cost. Our problem, called k-Preemptive bipartite scheduling (KPBS) is proven to be NP-Complete. Moreover we prove that approximating KPBS problem within a ratio number smaller that $\frac{4}{3}$ is impossible unless P=NP. In spite of this negative result, we study a lower bound on the cost of KPBS problem in terms of its parameters, and we propose an approximation algorithm with ratio 2 and fast heuristics.</div>
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