1,720,979 research outputs found
Benchmarking data collected on CloudLab
No full textThis dataset includes over 6.4M performance measurements collected on the CloudLab testbed. For more information about *how* and *why* it is collected, please refer to the "Taming Performance Variability" paper (https://www.usenix.org/system/files/osdi18-maricq.pdf). For additional information about CPU measurements, you can refer to: https://www.flux.utah.edu/download?uid=288.
The dataset is split into 3 files, for CPU (1.9M records), memory (4.2M records), and disk (429K) results. All these records were exported from the live database dedicated to this benchmarking project on 02/07/2020.
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Contributors:
- Dmitry Duplyakin
- Alexandru Uta
- Aleksander Maricq
- Robert Ricci</p
alexandru-uta/cloud_network_variability_data: Cloud Network Variability Data
No full text# Dataset on Cloud Network Variability
This is the dataset obtained while benchmarking public and private clouds for the following article:
### Alexandru Uta, Alexandru Custura, Dmitry Duplyakin, Ivo Jimenez, Jan Rellermeyer, Carlos Maltzahn, Robert Ricci, Alexandru Iosup. Is Big Data Performance Reproducible in Modern Cloud Networks?. In proceedings of 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2020, February 25-27, Santa Clara, USA.
The dataset contains bandwidth variability data for:
- Amazon EC2
- Google Compute Engine
- Microsoft Azure (limited data)
- Scaleway (limited data)
- SURFsara HPCCloud
The dataset contains TCP latency (RTT) data for:
- Amazon EC2
- Google Compute Engine
The dataset contains data regarding token bucket sizes (explained in depth in the aforementioned article) for Amazon EC2.
Please note that the full archive is over 3.5 GB of data, made up of hundreds of thousands of small files. This is why we decided to archive the data, which we then split into smaller files, to accommodate for the Github max file size of 100 MB.
===== DETAILS ON THE ARCHIVE FORMAT =====
1. The Bandwidth Variability data:
- archived in the bandwidth_variability_data.tar.bz2.parta, .partb, .partc
- after unpacking the archive, the data is split in directories per machine type, and experiment type, for example:
--- perfvar-aws-m5xlarge-fullspeed: contains iperf3 output files for continuous communication between 2 m5.xlarge VMs in Amazon EC2.
--- perfvar-google-4cpu-bursty-5s30s: contains iperf3 output files for bursty communication (5 seconds communication, 30 seconds break; repeat)
2. The Latency Variability data:
- archived in the file latency_study.tar.bz2
- after unpacking the archive, the directories contain TCP dump RTT data and iperf3 outputs
3. The Token Bucket AWS study:
- archived in the file token_bucket_study.tar.bz2
- contains files of form INSTANCE_TYPE-REGION-TIMESTAMP.{bw, raw, tb}
- files with extension .raw contain raw iperf3 client output
- files with extension .bw contain bandwidth samples taken at 1 second intervals from the iperf3 utility
- files with extension .tb contain a triple of form
- example of a file name: c5.2xlarge-us-west-1-1567733720.ra
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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