Energy-saving self-configuring networked data centers

What is it about?

In this paper, we develop the optimal minimum-energy scheduler for the dynamic online joint allocation of the task sizes, computing rates, communication rates and communication powers in virtualized Networked Data Centers (NetDCs) that operates under hard per-job delay-constraints. The resulting optimal scheduler is amenable of scalable and distributed online implementation and its analytical characterization is in closed-form. After numerically testing its actual performance under randomly-time

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Why is it important?

We propose a new mathematical techniques to control the frequency, workload, and communication rates of the VMs of data-centers for online jobs to minimize energy consumption of computation, communication and the switching time/cost among the grain-jobs in real systems. We solve this problem mathematically and compare it with 2 state-of-the arts works in green technology of data-centers. The main objective is that, approach is irrespective of the jobs ordering as workloads with low time-ordering