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Here, firstly we create a set of files and data node to generate a population by assigning the file to data node randomly and evaluate the fitness which is minimizing the objective function. Secondly, we regenerate the population to produce optimal or suboptimal population using OGSA. The experimental results show that the performance of the proposed methods is better than the other methods of data replication problem.<\/p>","DOI":"10.4018\/ijeis.2020010104","type":"journal-article","created":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T04:50:03Z","timestamp":1575003003000},"page":"69-91","source":"Crossref","is-referenced-by-count":2,"title":["An Efficient Multi-Objective Model for Data Replication in Cloud Computing Environment"],"prefix":"10.4018","volume":"16","author":[{"given":"K.","family":"Sasikumar","sequence":"first","affiliation":[{"name":"BITS Pilani, Dubai, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B.","family":"Vijayakumar","sequence":"additional","affiliation":[{"name":"BITS Pilani, Dubai, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"issue":"1","key":"IJEIS.2020010104-0","first-page":"4","article-title":"A Taxonomy of Partitioned Replicated Cloud-based Database Systems.","volume":"38","author":"D.Agrawal","year":"2015","journal-title":"IEEE Data Eng. 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