[hpc-announce] [Call for Papers][Energies]: Special Issue "Cloud Computing Systems and Energy Efficient Utilization"

[Alexey Lastovetsky]

Energies Special Issue Information
(https://www.mdpi.com/journal/energies/special_issues/cloud_computing_energy_efficient)

Dear Colleagues,

In the current digital era, computing is prevalent, and the level of 
penetration of computing in society, industry, economy, science, and 
engineering will only increase. Therefore, the energy involved in 
computing—which was not considered a big issue in the past—is becoming a 
grand technological challenge. The proportion of total energy consumption 
represented by ICT is rapidly increasing. By 2030, it is predicted to 
consume around 50% of all the generated electricity, according to some 
prognoses. This situation is not sustainable, and extraordinary efforts are 
needed to increase energy efficiency in ICT.

Cloud computing systems have demonstrated exponential growth over the last 
decade and quickly become the dominant computing infrastructure. By the end 
of 2020, two-thirds of enterprise infrastructure will be cloud-based; 
additionally, 82% of the workload will reside in the cloud 
(https://techjury.net/stats-about/cloud-computing/). Therefore, any 
improvements in the energy efficiency of cloud systems will also improve the 
global energy efficiency of computing.

This Special Issue invites submissions addressing all aspects of energy 
efficiency in cloud computing systems at all levels. Manuscripts reporting 
accurate application-level power and energy predictive models, and energy 
measurement methods and tools are particularly welcome. Methods on the 
optimization of multiple objectives are also welcome but must include energy 
consumption as one of the primary objectives.

Alexey Lastovetsky
Guest Editor

Energies (ISSN 1996-1073; CODEN: ENERGA) is a peer-reviewed open access 
journal of related scientific research, technology development, engineering, 
and the studies in policy and management and is published semi-monthly 
online by MDPI.
Impact Factor: 2.707 (2018) ; 5-Year Impact Factor: 2.990 (2018)

Open Access free for readers, with article processing charges (APC) paid by 
authors or their institutions.
High visibility: indexed by the Science Citation Index Expanded (Web of 
Science), Ei Compendex, Scopus and other databases.
Rapid publication: manuscripts are peer-reviewed and a first decision 
provided to authors approximately 17.1 days after submission; acceptance to 
publication is undertaken in 2.9 days (median values for papers published in 
this journal in the second half of 2019).


Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and 
logging in to this website. Once you are registered, click here to go to the 
submission form. Manuscripts can be submitted until the deadline. All papers 
will be peer-reviewed. Accepted papers will be published continuously in the 
journal (as soon as accepted) and will be listed together on the special 
issue website. Research articles, review articles as well as short 
communications are invited. For planned papers, a title and short abstract 
(about 100 words) can be sent to the Editorial Office for announcement on 
this website.

Submitted manuscripts should not have been published previously, nor be 
under consideration for publication elsewhere (except conference proceedings 
papers). All manuscripts are thoroughly refereed through a single-blind 
peer-review process. A guide for authors and other relevant information for 
submission of manuscripts is available on the Instructions for Authors page. 
Energies is an international peer-reviewed open access semimonthly journal 
published by MDPI.

Please visit the Instructions for Authors page before submitting a 
manuscript. The Article Processing Charge (APC) for publication in this open 
access journal is 1800 CHF (Swiss Francs). Submitted papers should be well 
formatted and use good English. Authors may use MDPI's English editing 
service prior to publication or during author revisions.

Keywords
energy of computing
cloud computing
energy efficient computing
energy predictive models
measurement of energy of computing
Published Papers
This special issue is now open for submission.