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Towards Predictive Self-optimization by Situation Recognition

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dc.contributor.authorGötz, Sebastian
dc.contributor.authorSchöne, René
dc.contributor.authorWilke, Claas
dc.contributor.authorMendez, Julian
dc.contributor.authorAßmann, Uwe
dc.date.accessioned2017-12-06T09:23:57Z
dc.date.available2017-12-06T09:23:57Z
dc.date.issued2013
dc.description.abstractEnergy efficiency of software is an increasingly important topic. To achieve energy efficiency, a system should automatically optimize itself to provide the best possible utility to the user for the least possible cost in terms of energy consumption. To reach this goal, the system has to continuously decide whether and how to adapt itself, which takes time and consumes energy by itself. During this time, the system could be in an inefficient state and waste energy. We envision the application of predictive situation recognition to initiate decision making before it is actually needed. Thus, the time of the system being in an inefficient state is reduced, leading to a more energyefficient reconfiguration.en
dc.identifier.doi10.1007/s40568-013-0022-4
dc.identifier.pissn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/8774
dc.language.isoen
dc.publisherKöllen Druck & Verlag GmbH
dc.relation.ispartofSoftwaretechnik-Trends: Vol. 33, No. 2
dc.relation.ispartofseriesSoftwaretechnik-Trends
dc.subjectDescription Logic
dc.subjectAmbient Intelligence
dc.subjectDecision Step
dc.subjectConcurrent User
dc.subjectContract Clause
dc.titleTowards Predictive Self-optimization by Situation Recognitionen
dc.typeText/Journal Article
gi.citation.endPage9
gi.citation.startPage8

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Softwaretechnik-Trends 33(2) - 2013