dorsal/arxiv
View SchemaFractal Analysis On Internet Traffic Time Series
| Authors | K. B. Chong, K. Y. Choo |
|---|---|
| Categories | |
| ArXiv ID | physics/0206012 |
| URL | https://arxiv.org/abs/physics/0206012 |
Abstract
Fractal behavior and long-range dependence have been observed in tele-traffic measurement and characterization. In this paper we show results of application of the fractal analysis to internet traffic via various methods. Our result demonstrate that the internet traffic exhibits self-similarity. Time-scale analysis show to be an effective way to characterize the local irregularity. Based on the result of this study, these two Internet time series exhibit fractal characteristic with long-range dependence.
{
"annotation_id": "ef667c77-0d3e-4d20-b18f-3122dcc85ff6",
"date_created": "2026-03-02T18:00:39.481000Z",
"date_modified": "2026-03-02T18:00:39.481000Z",
"file_hash": "30e4aaa00d45795ddda691459b976ef301508c2b9456bb9d249823da9b59379a",
"private": false,
"record": {
"abstract": "Fractal behavior and long-range dependence have been observed in tele-traffic\nmeasurement and characterization. In this paper we show results of application\nof the fractal analysis to internet traffic via various methods. Our result\ndemonstrate that the internet traffic exhibits self-similarity. Time-scale\nanalysis show to be an effective way to characterize the local irregularity.\nBased on the result of this study, these two Internet time series exhibit\nfractal characteristic with long-range dependence.",
"arxiv_id": "physics/0206012",
"authors": [
"K. B. Chong",
"K. Y. Choo"
],
"categories": [
"physics.comp-ph",
"physics.data-an"
],
"title": "Fractal Analysis On Internet Traffic Time Series",
"url": "https://arxiv.org/abs/physics/0206012"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "28c174d0-1394-4de5-bc42-b9f9f20cb7a2",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}