Towards an Optimized Energy Consumption of Resources in Cloud Data Centers

Abstract

Over the last few years, cloud computing has become a prominent paradigm. It promises to offer to users cost-effective and on-demand decentralized services, in terms of computing, memory, storage, etc., without the need for large infrastructure investments. Moreover, with the growing number of data centers resources, much higher levels of energy are being consumed. Also, the increasing level of associated carbon dioxide is emitted in the air, which consequently, raises the costs. Considering that there is an extreme growth in demand for Data Centers cloud computing requiring high computational complexity, there is an utmost need to take sufficient measures to lower the risk of energy demand. Hence, efficient energy-aware techniques are required to assure proper performance with regards to Service Level Agreements (SLA). In this work, we highlighted the issue of Virtual Machines (VMs) allocation in cloud computing data centers, and how to better manage the placement of VMs in order to optimize performance and reduce energy consumption. In our proposed solution, we will focus on minimizing the number of Physical Machines (PMs) hosting the VMs and utilize them as sufficient as possible.