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Under the condition of considering the task priority, the algorithm leverages the execution time of tasks for greedy strategy, and binding large task and small task in the task list to form \u201ctask pair\u201d to perform scheduling, so as to effectively solve the problem of unbalanced load. To reduce the average response time of tasks, the algorithm priority schedules the small task from the \u201ctask pair\u201d. The experimental results show that, compared with the Min-Min and P-Min-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and saves the total execution time for tasks. Compared with Max-Min and P-Max-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and reduces the total completion time and average response time.<\/jats:p>","DOI":"10.3233\/jifs-179299","type":"journal-article","created":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T10:42:54Z","timestamp":1562064174000},"page":"4647-4655","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["A novel task scheduling algorithm integrated with priority and greedy strategy in cloud computing"],"prefix":"10.1177","volume":"37","author":[{"given":"Zhou","family":"ZHOU","sequence":"first","affiliation":[{"name":"School of Computer Engineering and Applied Mathematics, Changsha University, Changsha, China"}]},{"given":"Houliang","family":"Xie","sequence":"additional","affiliation":[{"name":"Information Engineering Department, Zhangjiajie Institute of Aeronautical Engineering, Zhangjiajie, China"}]},{"given":"Fangmin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Applied Mathematics, Changsha University, Changsha, China"}]}],"member":"179","published-online":{"date-parts":[[2019,6,27]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.09.014"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2732458"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-018-3403-7"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2016.2623803"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.4942"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2015.2476459"},{"key":"e_1_3_2_8_2","first-page":"848","article-title":"A Task Scheduling Strategy Based onWeighted Round-Robin for Distributed Crawler","author":"Ge D.","year":"2014","unstructured":"GeD. and DingZ., A Task Scheduling Strategy Based onWeighted Round-Robin for Distributed Crawler, 2014 IEEE\/ACM 7th International Conference on Utility and Cloud Computing (2014), 848\u2013852.","journal-title":"2014 IEEE\/ACM 7th International Conference on Utility and Cloud Computing"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-015-0530-0"},{"key":"e_1_3_2_10_2","author":"Etminani K.","year":"2007","unstructured":"EtminaniK. and NaghibzadehM.A., min-min max-min selective algorihtm for grid task scheduling, In: 3th IEEE\/IFIP International Conference in Central Asia on Internet, Tashkent 2007.","journal-title":"min-min max-min selective algorihtm for grid task scheduling, In: 3th IEEE\/IFIP International Conference in Central Asia on Internet"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.07.028"},{"key":"e_1_3_2_12_2","first-page":"87","article-title":"An analysis of the \u201cUniversal suffrage\u201d selection operator","volume":"4","author":"Filippo N.","year":"2014","unstructured":"FilippoN. and LorenzaS., An analysis of the \u201cUniversal suffrage\u201d selection operator, Evolutionary Computation 4 (2014), 87\u2013107.","journal-title":"Evolutionary Computation"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2015.2439695"},{"key":"e_1_3_2_14_2","first-page":"1","article-title":"A PSO-based task scheduling algorithm improved using a load-balancing technique for the cloud computing environment","volume":"30","author":"Ebadifard F.","year":"2017","unstructured":"EbadifardF. and BabamirS.M., A PSO-based task scheduling algorithm improved using a load-balancing technique for the cloud computing environment, Concurrency & Computation Practice & Experience 30 (2017), 1\u201316.","journal-title":"Concurrency & Computation Practice & Experience"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2013.10.017"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.05.056"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-017-2766-x"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2011.2161090"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1934784"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2012.05.028"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1002\/spe.995"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.4970"}],"container-title":["Journal of Intelligent &amp; 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