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DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

Overview of attention for article published in Journal of Big Data, March 2021
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Mentioned by

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1 X user

Citations

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16 Dimensions

Readers on

mendeley
16 Mendeley
Title
DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing
Published in
Journal of Big Data, March 2021
DOI 10.1186/s40537-021-00437-7
Authors

Hossein Ahmadvand, Fouzhan Foroutan, Mahmood Fathy

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 19%
Unspecified 1 6%
Lecturer 1 6%
Librarian 1 6%
Student > Ph. D. Student 1 6%
Other 1 6%
Unknown 8 50%
Readers by discipline Count As %
Engineering 2 13%
Computer Science 2 13%
Business, Management and Accounting 1 6%
Unspecified 1 6%
Environmental Science 1 6%
Other 1 6%
Unknown 8 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 March 2021.
All research outputs
#18,791,778
of 23,287,285 outputs
Outputs from Journal of Big Data
#269
of 351 outputs
Outputs of similar age
#317,644
of 422,656 outputs
Outputs of similar age from Journal of Big Data
#10
of 16 outputs
Altmetric has tracked 23,287,285 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 351 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 422,656 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.