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Considering these aspects, the proposed clustering agent-based model improves energy saving by efficient allocation of the VMs to the hosting servers, which reduces the response time for initial allocation. Middle VM migration (MVM) strategy for server consolidation minimizes the number of VM migrations. Further, randomization of extra resource requirement done to cater to real-time scenarios needs more resource requirements than the initial requirement. Simulation results show that the proposed approach reduces the number of migrations and response time for user request and improves energy saving in the cloud environment.<\/p>","DOI":"10.4018\/ijiit.2019010104","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T07:50:51Z","timestamp":1547711451000},"page":"84-100","source":"Crossref","is-referenced-by-count":5,"title":["Energy Efficient Load Balancing in Cloud Data Center Using Clustering Technique"],"prefix":"10.4018","volume":"15","author":[{"given":"N.","family":"Thilagavathi","sequence":"first","affiliation":[{"name":"Anna University, Chennai, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"D. 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