{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:22:11Z","timestamp":1781104931244,"version":"3.54.1"},"reference-count":30,"publisher":"IGI Global Scientific Publishing","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<p>Cloud computing has opened new avenues in the computing resource provisioning. It is providing affordable computing services to the users and opportunities to the cloud service providers to scale up their business. However, the upscaling resulted in the creation of huge datacenters running round the clock. Energy consumption in these datacenters is becoming a burning issue due to environmental hazards and operating costs. A novel method using dynamic threshold has been proposed in this article. Thresholds are used to migrate the virtual machines (VM) on physical machines (PM) for consolidation. A dynamic threshold selection method is used to reduce energy consumed by physical machines of the data centers. The upper and lower thresholds are set dynamically based upon the previous pattern of the CPU utilization. Experiments conducted on PlanetLab data show significant improvement in the energy efficiency without compromising SLA.<\/p>","DOI":"10.4018\/ijsi.2020040104","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T14:52:12Z","timestamp":1581087132000},"page":"54-67","source":"Crossref","is-referenced-by-count":3,"title":["A Dynamic Threshold Based Energy Efficient Method for Cloud Datacenters"],"prefix":"10.4018","volume":"8","author":[{"family":"Shally","sequence":"first","affiliation":[{"name":"Banasthali Vidyapith, Rajasthan, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanjay Kumar","family":"Sharma","sequence":"additional","affiliation":[{"name":"Banasthali Vidyapith, Rajasthan, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4617-704X","authenticated-orcid":true,"given":"Sunil","family":"Kumar","sequence":"additional","affiliation":[{"name":"Manipal University Jaipur, Jaipur, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJSI.2020040104-0","doi-asserted-by":"publisher","DOI":"10.1109\/ccgrid.2010.45"},{"issue":"13","key":"IJSI.2020040104-1","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1002\/cpe.1867","article-title":"Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers.","volume":"24","author":"A.Beloglazov","year":"2012","journal-title":"Concurrency and Computation"},{"key":"IJSI.2020040104-2","doi-asserted-by":"publisher","DOI":"10.1145\/2208828.2208853"},{"key":"IJSI.2020040104-3","first-page":"109","article-title":"Report to Congress on Server and Data Center Energy Efficiency.","author":"R.Brown","year":"2007","journal-title":"Public Law"},{"key":"IJSI.2020040104-4","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2008"},{"issue":"1","key":"IJSI.2020040104-5","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1002\/spe.995","article-title":"CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms.","volume":"41","author":"R. 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