NDLI: Evaluating a cloud federation ecosystem to reduce carbon footprint by moving computational resources

Content Provider	IEEE Xplore Digital Library
Author	Giacobbe, Maurizio Celesti, Antonio Fazio, Maria Villari, Massimo Puliafito, Antonio
Copyright Year	2015
Description	Author affiliation: DICIEAMA, University of Messina, Contrada di Dio - 98166 Messina, Italy (Giacobbe, Maurizio; Celesti, Antonio; Fazio, Maria; Villari, Massimo; Puliafito, Antonio)
Abstract	Cloud federation is an emerging topic towards new dynamic scenarios in smart ecosystems, where new more flexible energy management strategies are needed than the traditional, in order to optimize mobility and energy efficiency. In this paper we focus both on cloud federation and energy efficiency to enforce a dynamic energy management strategy for the whole ecosystem, in order to reduce carbon dioxide emissions. More specifically, starting from our two-step approach, we evaluate a cloud federation ecosystem by moving computational resources among federated cloud DCs in order to maintain, for a forecast period, the related workload at the best Green Destination (GD) powered by renewable energy sources. To this end we present and discuss two simulated scenarios, and their experimental results, thus to proving the goodness of our approach. Moreover, an energy comparison between the transfer and the maintenance phases for the computational workload is made.
Starting Page	99
Ending Page	104
File Size	379867
Page Count	6
File Format	PDF
e-ISBN	9781467371940
DOI	10.1109/ISCC.2015.7405500
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-06
Publisher Place	Cyprus
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cloud computing Power demand Ecosystems Green products Renewable energy sources Carbon dioxide Computational Resources Mobility Cloud Computing Federation Virtual Machine Migration Energy Sustainability Green Computing
Content Type	Text
Resource Type	Article

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