Evidence map›Paper›PMID 27219671›Full record

ArticlePloS one2016

Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs.

Carlos F Alvarez, Luis E Palafox, Leocundo Aguilar, Mauricio A Sanchez, Luis G Martinez

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Carlos F AlvarezFaculty of Chemical Sciences and Engineering, Autonomous University of Baja California, Baja California, Tijuana, Mexico.ORCID 0000-0002-8985-9545
Luis E PalafoxFaculty of Chemical Sciences and Engineering, Autonomous University of Baja California, Baja California, Tijuana, Mexico.
Leocundo AguilarFaculty of Chemical Sciences and Engineering, Autonomous University of Baja California, Baja California, Tijuana, Mexico.
Mauricio A SanchezFaculty of Chemical Sciences and Engineering, Autonomous University of Baja California, Baja California, Tijuana, Mexico.
Luis G MartinezFaculty of Chemical Sciences and Engineering, Autonomous University of Baja California, Baja California, Tijuana, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node's behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder.

Indexed as

Computer Communication NetworksWireless TechnologyAlgorithmsComputer SimulationEntropyModels, Theoretical

Identifiers

PMID27219671
PMCPMC4878810

What OpenQuestion holds

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LicenceCC BY
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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.