Research Area:  Cloud Computing

Abstract:

A widespread use of the cloud computing paradigm has increased the necessity and significance of improving the management efficiency of cloud infrastructures. Special attention is paid to solving cloud resource management problems. In this paper, authors present an architecture of Software Defined Cloud Infrastructure management system that leverages Software Defined approach in all subsystems: network, storage, and computation. Due to the intensive changes of virtual machine (VM) workloads and different conditions of resource utilization the VM placement and migration problems should be solved and optimized continuously in an online manner. To address such problems the authors propose novel heuristics for VM placement and consolidation based on a physical machine (PM) workload prediction. The authors also evaluate a particular policy of the VM allocation in a data center using an adaptive genetic algorithm. The proposed adaptive Software Defined approach to the cloud infrastructure management is implemented by using the policy selector that allows to select different algorithms or policies for resources and virtual machines management in order to adapt to the impact of disturbing influences.

Keywords:  

Author(s) Name:  Sergii Telenyk; Eduard Zharikov; Oleksandr Rolik

Publisher name:  IEEE

DOI:  10.1109/STC-CSIT.2016.7589859

Volume Information:  Volume 2016

Paper Link:   https://ieeexplore.ieee.org/abstract/document/7589859