Abstract
Cloud 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 (TCA: BF) and first fit (TCA: FF) scheduling algorithms. Extensive simulation is performed to validate the superiority of the proposed approach compared to some existing ones.
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