Probabilistic Estimation of Response Times Through Large Deviations
Identifieur interne : 004633 ( Main/Exploration ); précédent : 004632; suivant : 004634Probabilistic Estimation of Response Times Through Large Deviations
Auteurs : Nicolas Navet [France] ; Liliana Cucu [France] ; René Schott [France]Source :
Abstract
We apply large deviation theory to assess the probability that the average, or the sum, of the response times of a sequence of consecutive aperiodic jobs is below a given threshold. This coarse-grained performance metric is for instance adapted to evaluate the responsiveness of a soft-real system or the freshness of input data consumed by an algorithm. The technique proposed works with distribution of response times as input but does not require that the distribution obeys a closed-form equation. Indeed, it can accept empirical distributions given under the form of frequency histograms obtained, for instance, by monitoring the system. Future work should be devoted to further assess the applicability of the proposal and relax some technical assumptions.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
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Le document en format XML
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type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author><author><name sortKey="Schott, Rene" sort="Schott, Rene" uniqKey="Schott R" first="René" last="Schott">René Schott</name><affiliation wicri:level="1"><hal:affiliation type="researchteam" xml:id="struct-2406" status="OLD"><idno type="RNSR">200218298K</idno><orgName>Real time and interoperability</orgName><orgName type="acronym">TRIO</orgName><desc><address><country key="FR"></country></address><ref type="url">http://www.inria.fr/equipes/trio</ref></desc><listRelation><relation active="#struct-160" type="direct"></relation><relation name="UMR7503" active="#struct-441569" type="indirect"></relation><relation active="#struct-300009" 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type="indirect"><org type="institution" xml:id="struct-300291" status="OLD"><orgName>Université Henri Poincaré - Nancy 1</orgName><orgName type="acronym">UHP</orgName><date type="end">2011-12-31</date><desc><address><addrLine>24-30 rue Lionnois, BP 60120, 54 003 NANCY cedex, France</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300292" type="indirect"><org type="institution" xml:id="struct-300292" status="OLD"><orgName>Université Nancy 2</orgName><date type="end">2011-12-31</date><desc><address><addrLine>91 avenue de la Libération, BP 454, 54001 Nancy cedex</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300293" type="indirect"><org type="institution" xml:id="struct-300293" status="OLD"><orgName>Institut National Polytechnique de Lorraine</orgName><orgName type="acronym">INPL</orgName><date type="end">2011-12-31</date><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-2496" type="direct"><org type="laboratory" xml:id="struct-2496" status="OLD"><orgName>INRIA Lorraine</orgName><desc><address><addrLine>615 rue du Jardin Botanique 54600 Villers-lès-Nancy</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/centre-de-recherche-inria/nancy-grand-est</ref></desc><listRelation><relation active="#struct-300009" type="direct"></relation></listRelation></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université Nancy 2</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We apply large deviation theory to assess the probability that the average, or the sum, of the response times of a sequence of consecutive aperiodic jobs is below a given threshold. This coarse-grained performance metric is for instance adapted to evaluate the responsiveness of a soft-real system or the freshness of input data consumed by an algorithm. The technique proposed works with distribution of response times as input but does not require that the distribution obeys a closed-form equation. Indeed, it can accept empirical distributions given under the form of frequency histograms obtained, for instance, by monitoring the system. Future work should be devoted to further assess the applicability of the proposal and relax some technical assumptions.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Nancy</li></settlement><orgName><li>Institut national polytechnique de Lorraine</li><li>Université Nancy 2</li><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="Navet, Nicolas" sort="Navet, Nicolas" uniqKey="Navet N" first="Nicolas" last="Navet">Nicolas Navet</name></region><name sortKey="Cucu, Liliana" sort="Cucu, Liliana" uniqKey="Cucu L" first="Liliana" last="Cucu">Liliana Cucu</name><name sortKey="Schott, Rene" sort="Schott, Rene" uniqKey="Schott R" first="René" last="Schott">René Schott</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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