Architecture and Conceptual Bases of Cloud IT Infrastructure Management

Abstract

A widespread use of the cloud computing paradigm has increased the necessity and significance of improving the management efficiency of cloud infrastructures. Cloud infrastructures are characterized by a large amount of resources, different virtualization technology usage, increasing complexity, the substantial dynamics of technological changes, increasing volume of processed information. Under these conditions, special attention is paid to solving cloud resource management problems. In this paper, the 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 present an algorithm for continuous new VM allocation and VM migration. Furthermore, the authors propose novel heuristics for VM placement and consolidation based on a physical machine (PM) workload prediction and evaluate a particular policy of the VM allocation in a data center using the adaptive genetic algorithm. The proposed Adaptive Software Defined approach to the cloud infrastructure management is implemented in the policy selector, and takes into account the existing API of SDN, Software Defined Storage, and Software Defined Computing controllers. This allows to select different algorithms or policies for resources and virtual machines management in order to adapt to the impact of disturbing influences.