Intensive computation in tasks such as weather forecasting and scientific solar system exploration requires high-speed processors and huge data storage. Very large data centers are likely to consume more energy as the number of servers substantially increases. Perhaps cloud computing technology that supports virtual machines (VMs) and virtualization practices, such as infrastructure as a service (IaaS), might reduce energy consumption. Atiewi et al. investigate the impact of two task scheduling algorithms on energy efficiency utilization in virtualized settings. They install and configure an extension of the NS2 network simulator, called the GreenCloud simulator, and then use it to construct a data center and a cloud network, link the data centers to the VMs, create processing requests and requirements of cloud users on the VMs, and monitor and compute metrics that impact energy consumption on cloud computers.
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