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Scheduling Virtual Data Along with Data Servers: Case Study

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Advances in Data Science and Management

Abstract

It has been observed that cloud computing environments sometimes may provide significant benefits, including reconfiguring virtualized resources on demand, which may be very much beneficial toward deploying cloud services. Earlier, particularly in traditional data centers, usually, applications may be tied to specific physical servers to deal with the upper-bound assigned tasks. In that case, the data centers may be expensive to maintain low resource utilization associated with virtual technology. Of course, the cloud data centers are more flexible and secure while providing better support for on-demand allocation as well. It may improve server utilization and signifies appropriate virtualization technology. As the cost of current data centers may be mostly driven by their energy consumption, sometimes challenges may have to be faced regarding the cost of energy per each virtual machine while being associated with heterogeneous environment. Practically, while designing the private cloud, major challenges associated with cloud computing environment may be faced. As in this consideration, each virtual machine may be mapped toward the physical host in accordance with the available resource on the host machine, accordingly, quantifying the performance of scheduling, and allocating cloud infrastructure may be extremely challenging. In this paper, focused is on virtualized data and evaluation mechanisms associated with data servers as well as data centers.

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Correspondence to Patra Prakash Chandra .

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Chandra, P.P., Anita, M., Kumar, M.S. (2020). Scheduling Virtual Data Along with Data Servers: Case Study. In: Borah, S., Emilia Balas, V., Polkowski, Z. (eds) Advances in Data Science and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-15-0978-0_25

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