Non-Preemptive Flow-Time Minimization via Rejections

May 24, 2018 Β· Declared Dead Β· πŸ› International Colloquium on Automata, Languages and Programming

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Authors Anupam Gupta, Amit Kumar, Jason Li arXiv ID 1805.09602 Category cs.DS: Data Structures & Algorithms Citations 1 Venue International Colloquium on Automata, Languages and Programming Last Checked 4 months ago
Abstract
We consider the online problem of minimizing weighted flow-time on unrelated machines. Although much is known about this problem in the resource-augmentation setting, these results assume that jobs can be preempted. We give the first constant-competitive algorithm for the non-preemptive setting in the rejection model. In this rejection model, we are allowed to reject an $\varepsilon$-fraction of the total weight of jobs, and compare the resulting flow-time to that of the offline optimum which is required to schedule all jobs. This is arguably the weakest assumption in which such a result is known for weighted flow-time on unrelated machines. While our algorithms are simple, we need a delicate dual-fitting argument to bound the flow-time while only a small fraction of elements are rejected.
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