Processing Resource Allocation in Cloud Networks

Diplomarbeiten (never - cancelled)

Betreuer

Alireza Zamani,

Abstract

Cloud Networks are known for their ability to accommodate the heavy processing required for the increasing data traffic. The concept aims to achieve performance gains by separating the baseband processing units (BBUs) from the remote radio heads (RRHs). Thanks to virtualization techniques, the baseband processing, can now be performed on virtual machines (VMs) which is a priceless tool for improving the processing efficiency, as it provides the opportunity for dynamic allocation and sharing of processing resources. In this work, we investigate the assignment of processing jobs and the allocation of processing resources among the virtual machines using machine learning techniques.

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