Energy-Constrained Resource Allocation and Scheduling in Cloud Computing

Abstract

In virtualized cloud computing systems, energy reduction is a major concern since it can provide many major benefits, such as reducing operating costs, increasing system efficiency, and protecting the environment. Typically, customers submit their appli- cations with millions of tasks executed in cloud data centers by thousands of high- performance servers installed. The cloud offers a variety of services through virtual machines (VMs). These latter usually consume a large amount of energy. Such energy consumption increases the cost of electricity and has a negative environmental effect. To maintain a better performance of the services offered by data centers and a reason- able energy consumption. A detailed study of the behavior of these systems is essential for the design of efficient optimization solutions to reduce energy consumption. This thesis work focuses on the development of a task scheduling model in order to minimize the energy consumption of data center resources while meeting customer requirements for quality of services.