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The concept of virtualization in cloud computing aims to maximize resource utilization and minimize cost by deploying multiple Virtual Machines (VMs) on a single physical server sharing resources such as CPU, Cache, I/O, and Memory. The sharing of these resources can cause severe performance degradation, thus requiring VM migration techniques for performance enhancement. The introduction of big data has made the performance enhancement more challenging due to extensive volume, velocity, variety, variability, and veracity of data. The existing VM performance and optimization challenges need to be optimized for big data use cases. This chapter presents big data triggered VM performance challenges focusing big data applications and storage migration in cloud computing. State of the art VM migration techniques are evaluated against challenges posed by big data to outline possible solutions and research challenges. |
