It is well known that cloud computing has many potential advantages over traditional\ndistributed systems. Many enterprises can build their own private cloud with open source\ninfrastructure as a service (IaaS) frameworks. Since enterprise applications and data are migrating to\nprivate cloud, the performance of cloud computing environments is of utmost importance for both\ncloud providers and users. To improve the performance, previous studies on cloud consolidation\nhave been focused on live migration of virtual machines based on resource utilization. However,\nthe approaches are not suitable for multimedia big data applications. In this paper, we reveal the\nperformance bottleneck of multimedia big data applications in cloud computing environments\nand propose a cloud consolidation algorithm that considers application types. We show that our\nconsolidation algorithm outperforms previous approaches.
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