A Novel Optimization Technique for Mastering Energy Consumption in Cloud Data Center

Cloud computing is one of the most popular technologies nowadays because of its wide utilities and various benefits in several IT companies all over the world. However, in front of the increasing users' requests for computing services, cloud providers are encouraged to deploy large data centers, which consumes very large amount of energy and contribute to,,,, high operational costs. Among the effects, carbon dioxide emission rate is growing each day due to the huge amount of power consumption. This energy efficiency is an important issue in cloud computing, mainly due to the required electrical power to run these systems and to cool them. Therefore, energy consumption has become a major concern for the widespread deployment of Cloud data centers. The growing importance for parallel applications in the Cloud introduces significant challenges in,,,, reducing energy consumption from hosted servers. This paper addresses the problem of placing independent applications on the physical servers (hosts) of a Cloud infrastructure. We proposed a novel heuristic to allocate applications so that total energy consumption is reduced. Our proposal respects various constraints e.g. the machines availability, capability and the duplication of applications. Experiments are illustrated to validate the potential of our approach.