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Linear time recursive algorithm, that schedules task among the local cores or between the local cores and the cloud with optimization for minimal-delay and energy consumption by the mobile device.

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Energy-and-Performance-Aware-Task-Scheduling-in-a-Mobile-Cloud-Computing-Environment

The high scientific applications which contain thousands of tasks are usually executed in virtualized cloud for many benefits. With the increment of the processing capability of the cloud system, the computation energy is significantly consumed along. Thus efficient energy consumption methods are quite necessary to save the energy cost. In this research project, the independent task scheduling problem in a cloud data center is considered. It is a big challenge to achieve the tradeoff between the minimization of computation energy and user defined deadlines.

The Linear time recursive algorithm represented in the research paper is implemented. The algorithim schedules task among the local cores or between the local cores and the cloud with optimization for minimal-delay and energy consumption by the mobile device.

The report attached displays the output we received and a clear explanation over how the results need to be interpretted.

Research paper & its report

https://github.com/SatishKumarAnbalagan/Energy-and-Performance-Aware-Task-Scheduling-in-a-Mobile-Cloud-Computing-Environment/blob/master/docs/Task_Scheduling_paper.pdf

https://github.com/SatishKumarAnbalagan/Energy-and-Performance-Aware-Task-Scheduling-in-a-Mobile-Cloud-Computing-Environment/blob/master/docs/report.pdf

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Linear time recursive algorithm, that schedules task among the local cores or between the local cores and the cloud with optimization for minimal-delay and energy consumption by the mobile device.

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