An Energy-efficient Task Scheduler in Virtualized Cloud Platforms

In cloud platforms, virtualization technology has been widely applied for deploying largescale IT-infrastructures due to its flexibility and extendibility. However, the extra software layer introduced by virtualization technology also raises many performance issues. One of them is the energy-efficiency losses when massive I/O-intensive tasks are running on virtualized servers. In this paper, we present a novel virtual machine scheduling approach, which the scheduler allows virtual machines to obtain extra CPU shares if they were frequently blocked by I/O interrupted recently. In this way, I/O-intensive tasks will have more chances of being scheduled so as to compensate their performance losses caused by I/O operations. Extensive experiments are conducted by using various benchmarks, and the results show that the proposed policy outperforms existing scheduling algorithm in the term of energy-efficiency especially when the virtualized system is in presence of intensive mixedworkloads.