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Decomposition analysis and machine learning in a workflow-forecast approach to the task scheduling problem for high-loaded distributed systems

The aim of this paper is to provide a description of machine learning based scheduling approach for high-loaded distributed systems that have patterns of tasks/queries that occur recurrently in workflow. The core of this approach is to predict the future workflow of the system depending on previous...

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Главные авторы: Gritsenko, A. V., Гриценко, А. В.
格式: Статья
语言:English
出版: Canadian Center of Science and Education 2019
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在线阅读:https://www.scopus.com/record/display.uri?eid=2-s2.0-84928547510&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=north+caucasus+federal+university&sid=c2b5101ac6f3f5921983751f044515f2&sot=afnl&sdt=sisr&cluster=scopubyr%2c%222015%22%2ct&sl=53&s=%28AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29%29&ref=%28Decomposition+analysis+and+machine+learning+in+a+workflow-forecast+approach+to+the+task+scheduling+problem+for+high-loaded+distributed+systems%29&relpos=0&citeCnt=5&searchTerm=
https://dspace.ncfu.ru/handle/20.500.12258/4255
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