Transmutations through cloud computing affect every aspect of computing; that could be measured in terms of performance. Furthermore, to support the performance enhancement in cloud environments “Virtualization” has been proved to be a notable evaluation. Additionally, in virtualization virtual machines are the instruments to harness the potential of cloud computing. Cloud infrastructure is shared among various users through virtualization. Virtualization enables applications of diverse nature to execute in isolation under distinct Virtual machines within a physical machine. Moreover, virtualization leverages higher utilization of physical resources. Among the said benefits of virtualization, live migration of VMs leads to the load balancing and energy saving benefits. Despite the said benefits of virtualization, violation of virtualization leads to the contention for the shared resources. Further, raising the performance interference issues. Conversely, limiting the interference leads to a higher demand for physical resources. Therefore, understanding the interference severity among the co-scheduled Virtual machines (VMs) has a great potential to improve the shared resources utilization. To investigate the interference and address the related challenges in this paper an in depth study has been carried out which covers the “interference source” to schedule the resource capacity in maximum by incorporating the bin-packing policies.
Key words: Systematic , Interference , Cloud , Computing , Environment
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