Scheduling Dags under Uncertainty

dc.creatorMalewicz, Grzegorz
dc.date2007-05-14
dc.date.accessioned2026-07-07T08:01:22Z
dc.date.available2026-07-07T08:01:22Z
dc.descriptionThis paper introduces a parallel scheduling problem where a directed acyclic graph modeling $t$ tasks and their dependencies needs to be executed on $n$ unreliable workers. Worker $i$ executes task $j$ correctly with probability $p_{i,j}$. The goal is to find a regimen $Σ$, that dictates how workers get assigned to tasks (possibly in parallel and redundantly) throughout execution, so as to minimize the expected completion time. This fundamental parallel scheduling problem arises in grid computing and project management fields, and has several applications. We show a polynomial time algorithm for the problem restricted to the case when dag width is at most a constant and the number of workers is also at most a constant. These two restrictions may appear to be too severe. However, they are fundamentally required. Specifically, we demonstrate that the problem is NP-hard with constant number of workers when dag width can grow, and is also NP-hard with constant dag width when the number of workers can grow. When both dag width and the number of workers are unconstrained, then the problem is inapproximable within factor less than 5/4, unless P=NP.
dc.identifierhttps://arxiv.org/abs/0705.1876
dc.identifierhttp://arxiv.org/abs/0705.1876
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/128890
dc.subjectData Structures and Algorithms
dc.subjectDiscrete Mathematics
dc.titleScheduling Dags under Uncertainty
dc.typetext

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