Abstract

Cloud computing is a new paradigm that offers computing resources in a virtualized way with unprecedented levels of flexibility, reliability, and scalability. The benefits of cloud computing, however, come at a high cost in terms of energy consumption, mainly because of one of the cloud’s core enablers, the data center. There are a number of proposals that seek to enhance the energy efficiency of data centers. Still, most of them focus on the energy consumed by CPU and ignore other important hardware components, e.g., RAM. In this paper, we show the considerable impact that RAM can have on the total energy consumption, particularly in servers with large amounts of this memory. We then propose two new approaches for dynamic consolidation of virtual machines in cloud data centers that take into account both CPU and RAM usage. We have implemented and evaluated our proposals in the CloudSim simulator using real-world traces and compared the results with other state-of-the-art solutions. By adopting a wider view of the system, our proposals can reduce not only energy consumption but also service level agreement (SLA) violations, thus providing a better service at a lower cost.

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