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Although cloud computing has gained sufficient popularity recently, there are still some key impediments to enterprise adoption. Cloud management is one of the top challenges. The ability of on-the-fly partitioning hardware resources into Virtual Machine (VM) instances facilitates elastic computing environment to users. But the extra layer of resource virtualization poses challenges on effective cloud management. The factors of time-varying user demand, complicated interplay between co-hosted VMs and the arbitrary deployment of multitier applications make it difficult for administrators to plan good VM configurations. In this paper, the authors propose a distributed learning mechanism that facilitates self-adaptive virtual machines resource provisioning.
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