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This algorithm is mainly split into two phases namely allocation of resources using SGO and shortest job first scheduling. The main aim is to map the jobs to virtual machines of cloud group to attain higher client satisfaction and lowest makespan time. Experiments are conducted on datasets and results are compared with present scheduling techniques. This model proved that this algorithm outrun the available algorithms based on concerned metrics.<\/p>","DOI":"10.4018\/ijncr.2018010102","type":"journal-article","created":{"date-parts":[[2018,4,24]],"date-time":"2018-04-24T08:49:23Z","timestamp":1524559763000},"page":"15-31","source":"Crossref","is-referenced-by-count":11,"title":["Client-Awareness Resource Allotment and Job Scheduling in Heterogeneous Cloud by Using Social Group Optimization"],"prefix":"10.4018","volume":"7","author":[{"family":"Phani Praveen S.","sequence":"first","affiliation":[{"name":"Research Scholar, Department of Computer Science, Bharathiar University, Coimbatore, India"}]},{"given":"K. Thirupathi","family":"Rao","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, K L Deemed to be University, Guntur, India"}]}],"member":"2432","reference":[{"key":"IJNCR.2018010102-0","doi-asserted-by":"crossref","unstructured":"Singh, D. P., Bhateja, V., Soni, S. K., & Shukla, A. K. (2014). 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