{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T10:23:51Z","timestamp":1770027831946,"version":"3.49.0"},"reference-count":41,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,8,11]]},"abstract":"<jats:p>Regarding the ever-increasing development of data and computational centers due to the contribution of high-performance computing systems in such sectors, energy consumption has always been of great importance due to CO2 emissions that can result in adverse effects on the environment. In recent years, the notions such as \u201cenergy\u201d and also \u201cGreen Computing\u201d have played crucial roles when scheduling parallel tasks in datacenters. The duplication and clustering strategies, as well as Dynamic Voltage and Frequency Scaling (DVFS) techniques, have focused on the reduction of the energy consumption and the optimization of the performance parameters. Concerning scheduling Directed Acyclic Graph (DAG) of a datacenter processors equipped with the technique of DVFS, this paper proposes an energy- and time-aware algorithm based on dual-phase scheduling, called EATSDCDD, to apply the combination of the strategies for duplication and clustering along with the distribution of slack-time among the tasks of a cluster. DVFS and control procedures in the proposed green system are mapped into Petri net-based models, which contribute to designing a multiple decision process. In the first phase, we use an intelligent combined approach of the duplication and clustering strategies to run the immediate tasks of DAG along with monitoring the throughput by concentrating on the reduction of makespan and the energy consumed in the processors. The main idea of the proposed algorithm involves the achievement of a maximum reduction in energy consumption in the second phase. To this end, the slack time was distributed among non-critical dependent tasks. Additionally, we cover the issues of negotiation between consumers and service providers at the rate of \u03bc based on Green Service Level Agreement (GSLA) to achieve a higher saving of the energy. Eventually, a set of data established for conducting the examinations and also different parameters of the constructed random DAG are assessed to examine the efficiency of our proposed algorithm. The obtained results confirms that our algorithm outperforms compared the other algorithms considered in this study.<\/jats:p>","DOI":"10.3233\/jifs-201696","type":"journal-article","created":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T14:43:29Z","timestamp":1624027409000},"page":"251-272","source":"Crossref","is-referenced-by-count":1,"title":["Distribution slack allocation algorithm for energy aware task scheduling in cloud datacenters"],"prefix":"10.1177","volume":"41","author":[{"given":"Golnaz","family":"Berenjian","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran"}]},{"given":"Homayun","family":"Motameni","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran"}]},{"given":"Mehdi","family":"Golsorkhtabaramiri","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran"}]},{"given":"Ali","family":"Ebrahimnejad","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran"}]}],"member":"179","reference":[{"issue":"6","key":"10.3233\/JIFS-201696_ref1","doi-asserted-by":"crossref","first-page":"5135","DOI":"10.3233\/JIFS-171927","article-title":"EATSDCD: A green Energy-aware scheduling algorithm for parallel Task-based application using clustering, duplication and DVFS technique in cloud datacenters","volume":"36","author":"Barzegar","year":"2019","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-201696_ref2","unstructured":"Koomey J. , Growth in data center electricity use to A report by Analytical Press, completed at the request of The New York Times, 9.2011 (2011), 161."},{"key":"10.3233\/JIFS-201696_ref3","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.future.2016.08.022","article-title":"Slack 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