Space-efficient scheduling of stochastically generated tasks

Tomáš Brázdil, Javier Esparza, Stefan Kiefer, Michael Luttenberger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 σ modeling the maximal space needed by the processor to store the currently active tasks when acting under the scheduler σ. We obtain tail bounds for the distribution of S σ for both offline and online schedulers, and investigate the expected value .

Original languageEnglish
Title of host publicationAutomata, Languages and Programming - 37th International Colloquium, ICALP 2010, Proceedings
Pages539-550
Number of pages12
EditionPART 2
DOIs
StatePublished - 2010
Event37th International Colloquium on Automata, Languages and Programming, ICALP 2010 - Bordeaux, France
Duration: 6 Jul 201010 Jul 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6199 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference37th International Colloquium on Automata, Languages and Programming, ICALP 2010
Country/TerritoryFrance
CityBordeaux
Period6/07/1010/07/10

Fingerprint

Dive into the research topics of 'Space-efficient scheduling of stochastically generated tasks'. Together they form a unique fingerprint.

Cite this