Simulation and Performance Analysis of Data Intensive and Workload Intensive Cloud Computing Data Centers

Data centers are becoming increasingly popular for the provisioning of computing resources. The cost and operational expenses of data centers have skyrocketed with the increase in computing capacity [1]. Energy consumption is a growing concern for data center operators. It is becoming one of the main entries on a data center operational expenses (OPEX) bill [2,3]. The Gartner Group estimates energy consumptions to account for up to 10% of the current OPEX, and this estimate is projected to rise to 50% in the next few years [4]. However, computing-based energy consumption is not the only power-related portion of the OPEX bill. High power consumption generates heat and requires an accompanying cooling system that costs in a range of $2–$5 million per year for classical data centers [5]. Failure to keep data center temperatures within operational ranges drastically decreases hardware reliability and may potentially violate the service level agreement (SLA) with the customers. From the perspective of energy efficiency, a cloud computing data center can be defined as a pool of computing and communication resources organized in the way to transform the received power into computing or data transfer work to satisfy user demands. The first power saving solutions focused on making the data center hardware components power efficient. Technologies, such as dynamic voltage and frequency scaling (DVFS), and dynamic power management (DPM) [6], were