Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 382

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Traffic dynamics based on local routing protocol on a scale-free network

Wang, Wen-Xu, Wang, Bing-Hong, Yin, Chuan-Yang, Xie, Yan-Bo, Zhou, Tao·2006·Physical Review E

Abstract

We propose a packet routing strategy with a tunable parameter based on the local structural information of a scale-free network. As free traffic flow on the communication networks is key to their normal and efficient functioning, we focus on the network capacity that can be measured by the critical point of phase transition from free flow to congestion. Simulations show that the maximal capacity corresponds to alpha= -1 in the case of identical nodes' delivering ability. To explain this, we investigate the number of packets of each node depending on its degree in the free flow state and observe the power law behavior. Other dynamic properties including average packets traveling time and traffic load are also studied. Inspiringly, our results indicate that some fundamental relationships exist between the dynamics of synchronization and traffic on the scale-free networks.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1103/physreve.73.026111

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 382

Metadata

Authors
Wang, W.-X., Wang, B.-H., Yin, C.-Y., Xie, Y.-B., & Zhou, T.
Venue
Physical Review E
Published
2006-02-10
Volume
73
Issue
2
Pages
026111-026111
ISSN
  • 1539-3755 (ISSN-L)
  • 1550-2376
OpenAlex
W1999261651
Cited by
382
References
1
FWCI
16.24
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Traffic dynamics based on local routing protocol on a scale-free network. https://app.cochat.ai/papers/10.1103/physreve.73.026111
The paper
Wang, W.-X., Wang, B.-H., Yin, C.-Y., Xie, Y.-B., & Zhou, T. (2006). Traffic dynamics based on local routing protocol on a scale-free network. Physical Review E. https://doi.org/10.1103/physreve.73.026111

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.