Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3216
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dc.contributor.authorSahoo, Sampa-
dc.contributor.authorSahu, Sahil Kumar-
dc.contributor.authorRath, Tanmay Kumar-
dc.contributor.authorSahoo, Bibhudatta-
dc.contributor.authorTuruk, Ashok Kumar-
dc.date.accessioned2019-01-22T05:00:55Z-
dc.date.available2019-01-22T05:00:55Z-
dc.date.issued2018-12-
dc.identifier.citation17th International Conference on Industrial Technology (ICIT 2018), Bhubaneswar, India, 20-22 December 2018.en_US
dc.identifier.urihttp://hdl.handle.net/2080/3216-
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractCloud computing is an emerging computing paradigm, where cloud resources are available according to the pay-per-use pricing model and can be scaled dynamically depending on the application needs. Noticeably, many real-time applications that demand both time and functional correctness are moving to cloud. So, it requires efficient use of cloud resources to support applications need. In this context, task scheduling is a well-known technique to achieve the performance improvement of applications running in clouds. Again, execution time and execution cost play a vital role in deciding an appropriate VM for execution of a real-time task. In this paper, we formulate the real-time task scheduling problem as a multi-constraint optimization problem with time and cost constraint. Further, proposed a solution through time and cost-efficient best fit (T CA : BF) and first fit (T CA : F F) scheduling algorithms. Extensive simulation is performed to validate the superiority of the proposed approach compared to some existing ones.en_US
dc.subjectCloud computingen_US
dc.subjectDeadlineen_US
dc.subjectExecution timeen_US
dc.subjectExecution costen_US
dc.subjectReal-time tasken_US
dc.titleTCA: A multi constraint real-time task scheduling algorithm for heterogeneous cloud environmenten_US
dc.typeArticleen_US
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