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- W4301423384 abstract "We study the problem of scheduling tasks for execution by a processor when the tasks can stochastically generate new tasks. Tasks can be of different types, and each type has a fixed, known probability of generating other tasks. We present results on the random variable S^sigma modeling the maximal space needed by the processor to store the currently active tasks when acting under the scheduler sigma. We obtain tail bounds for the distribution of S^sigma for both offline and online schedulers, and investigate the expected value of S^sigma." @default.
- W4301423384 created "2022-10-05" @default.
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- W4301423384 date "2010-04-24" @default.
- W4301423384 modified "2023-09-26" @default.
- W4301423384 title "Space-efficient scheduling of stochastically generated tasks" @default.
- W4301423384 doi "https://doi.org/10.48550/arxiv.1004.4286" @default.
- W4301423384 hasPublicationYear "2010" @default.
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