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Speed Up SchedulingAuthor: yash.guptaug08 Date: 2014-04-12 Report no: IIIT/TH/2014/7 Advisor:Kamalakar Karlapalem AbstractQueue is required when service provider is not able to handle jobs arriving over the time. In real life, job execution often requires human intervention in it’s execution. In a highly flexible and dynamic environment, some jobs might demand for faster execution especially when resources are limited and jobs are competing for acquiring resources. Thus, user may demand for speed up (reduced wait time / faster execution) for some of the jobs present in the queue at run time. In such cases, it is required to accelerate (directly sending the job to the server) jobs requesting for speed up ahead of other jobs present in the queue to facilitate earlier completion of urgent jobs. Since no additional resources are used, therefore such acceleration of jobs might result in slowing down of other jobs present in the queue. In this thesis, we model the problem of Speed Up Scheduling without acquiring any additional resources for the scheduling of on-line speed up requests posed by the user at run-time. Speed Up scheduling needs to speed up all the jobs that requested for it without unnecessarily slowing down the other jobs. Note that it might not be possible to achieve speed up for all the jobs that requested for it as well as it might be the case that while speeding up jobs, even some of the jobs that requested for speed up were slowed down. In order to address Speed Up problem, we provide implicit Speed Up techniques where the notion of acceleration is incorporated in the priority function. We use concepts of queuing theory and discrete event based simulation model for the design and evaluation of our speed up algorithms. We apply the idea of Speed Up Scheduling to two different applications - Web Scheduling and CPU Scheduling. We demonstrate our results with a simulation based model using trace driven workload and synthetic datasets to show the usefulness of Speed Up in these domains. We further examine how different scheduling algorithms can be compared based on speed up/slow down characteristics. Full thesis: pdf Centre for Data Engineering |
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