{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T22:08:20Z","timestamp":1770415700610,"version":"3.49.0"},"reference-count":27,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2012,5,11]],"date-time":"2012-05-11T00:00:00Z","timestamp":1336694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Cloud computing is an emerging technology where IT resources are virtualized to users as a set of a unified computing resources on a pay per use basis. The resources are dynamically chosen to satisfy a user Service Level Agreement and a required level of performance. Divisible load applications occur in many scientific and engineering applications and can easily be mapped to a Cloud using a master-worker pattern. However, those applications pose challenges to obtain the required performance. We model divisible load applications tasks processing on a set of cloud resources. We derive a novel model and formulas for computing the blocking probability in the system. The formulas are useful to analyze and predict the behavior of a divisible load application on a chosen set of resources to satisfy a Service Level Agreement before the implementation phase, thus saving time and platform energy. They are also useful as a dynamic feedback to a cloud scheduler for optimal scheduling. We evaluate the model in a set of illustrative scenarios.<\/jats:p>","DOI":"10.3390\/a5020289","type":"journal-article","created":{"date-parts":[[2012,5,11]],"date-time":"2012-05-11T11:06:37Z","timestamp":1336734397000},"page":"289-303","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Modeling and Performance Analysis to Predict the Behavior of a Divisible Load Application in a Cloud Computing Environment"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0946-1818","authenticated-orcid":false,"given":"Leila","family":"Ismail","sequence":"first","affiliation":[{"name":"Faculty of Information Technology, UAE University, 17551 Al-Maqam, Al-Ain, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liren","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, UAE University, 17551 Al-Maqam, Al-Ain, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,5,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Buyya, R., Yeo, C.S., and Venugopal, S. 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