Evidence map›Paper›PMID 30082595›Full record

ArticleSensors (Basel, Switzerland)2018

DIFTOS: A Distributed Infrastructure-Free Traffic Optimization System Based on Vehicular Ad Hoc Networks for Urban Environments.

Weidong Zhang, Nyothiri Aung, Sahraoui Dhelim, Yibo Ai

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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.

Weidong ZhangNational Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China. zwd@ustb.edu.cn.
Nyothiri AungSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China. nyothiriaung@xs.ustb.edu.cn.
Sahraoui DhelimSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China. sahraoui.dhelim@xs.ustb.edu.cn.
Yibo AiNational Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China. ybai@ustb.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aiming to alleviate traffic congestion, many congestion avoidance and traffic optimization systems have been proposed recently. However, most of them suffer from three main problems. Firstly scalability: they rely on a centralized server, which has to perform intensive communication and computational tasks. Secondly unpredictability: they use smartphones and other sensors to detect the congested roads and warn upcoming vehicles accordingly. In other words, they are used to solve the problem rather than avoiding it. Lastly, infrastructure dependency: they assume the presence of pre-installed infrastructures such as roadside unit (RSU) or cellular 3G/4G networks. Motivated by the above-mentioned reasons, in this paper, we proposed a fully distributed and infrastructure-less congestion avoidance and traffic optimization system for VANET (Vehicular Ad-hoc Networks) in urban environments named DIFTOS (Distributed Infrastructure-Free Traffic Optimization System), in which the city map is divided into a hierarchy of servers. The vehicles that are located in the busy road intersections play the role of servers, thus DIFTOS does not rely on any centralized server and does not need internet connectivity or RSU or any kind of infrastructure. As far as we know, in the literature of congestion avoidance using VANET, DIFTOS is the first completely infrastructure-free congestion avoidance system. The effectiveness and scalability of DIFTOS have been proved by simulation under different traffic conditions.

Indexed as

congestion avoidancedistributed serverintelligent transportation systemsITSpath planningtraffic optimizationVANET

Identifiers

PMID30082595
PMCPMC6111977

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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.