Evidence map›Paper›PMID 30417014›Full record

ArticleBioMed research international2018

Parallel MapReduce: Maximizing Cloud Resource Utilization and Performance Improvement Using Parallel Execution Strategies.

Ahmed Abdulhakim Al-Absi, Najeeb Abbas Al-Sammarraie, Wael Mohamed Shaher Yafooz, Dae-Ki Kang

Abstract read
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In one paragraph

Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ahmed Abdulhakim Al-AbsiDepartment of Smart Computing, Kyungdong University, Global Campus, 46 4-gil, Gosung, Gangwondo 24764, Republic of Korea.ORCID 0000-0001-6272-7756
Najeeb Abbas Al-SammarraieFaculty of Computer and Information Technology, Al-Madinah International University, 2 Jalan Tengku Ampuan Zabedah E/9E, 40100 Shah Alam, Selangor, Malaysia.
Wael Mohamed Shaher YafoozFaculty of Computer and Information Technology, Al-Madinah International University, 2 Jalan Tengku Ampuan Zabedah E/9E, 40100 Shah Alam, Selangor, Malaysia.
Dae-Ki KangDepartment of Computer & Information Engineering, Dongseo University, 47 Jurye-ro, Sasang-gu, Busan 47011, Republic of Korea.ORCID 0000-0002-4147-2835

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MapReduce is the preferred cloud computing framework used in large data analysis and application processing. MapReduce frameworks currently in place suffer performance degradation due to the adoption of sequential processing approaches with little modification and thus exhibit underutilization of cloud resources. To overcome this drawback and reduce costs, we introduce a Parallel MapReduce (

Indexed as

AlgorithmsCloud ComputingComputational BiologyModels, Theoretical

Identifiers

PMID30417014
PMCPMC6207866

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.