Green cloud computing with efficient resource allocation approach

Fei Cao, Michelle M. Zhu, Chase Q. Wu

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Due to the increasing deployment of data centers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with everincreasing problem complexity and big data size in the next decades, this chapter presents vision and challenges for energy-aware management of Cloud computing environments. We design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS). Furthermore, we also apply Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. The effectiveness of our algorithm is evaluated under various performance metrics and experimental scenarios using software adapted from open source CloudSim simulator.

Original languageEnglish
Title of host publicationGreen Services Engineering, Optimization, and Modeling in the Technological Age
PublisherIGI Global
Pages116-148
Number of pages33
ISBN (Electronic)9781466684485
ISBN (Print)146668447X, 9781466684478
DOIs
Publication statusPublished - 7 Jul 2015

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Cao, F., Zhu, M. M., & Wu, C. Q. (2015). Green cloud computing with efficient resource allocation approach. In Green Services Engineering, Optimization, and Modeling in the Technological Age (pp. 116-148). IGI Global. https://doi.org/10.4018/978-1-4666-8447-8.ch005