Modeling network traffic using generalized Cauchy process
Processes with long-range dependence (LRD) have gained wide applications in many fields of science and technologies ranging from hydrology to network traffic. Two key properties of such processes are LRD that is characterized by the Hurst parameter H and self-similarity (SS) that is measured by the...
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| Format: | Article |
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ELSEVIER SCIENCE BV
2008
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| Online Access: | http://shdl.mmu.edu.my/2749/ |
| _version_ | 1848790139224981504 |
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| author | LI, M LIM, S |
| author_facet | LI, M LIM, S |
| author_sort | LI, M |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | Processes with long-range dependence (LRD) have gained wide applications in many fields of science and technologies ranging from hydrology to network traffic. Two key properties of such processes are LRD that is characterized by the Hurst parameter H and self-similarity (SS) that is measured by the fractal dimension D. However, in the popular traffic model using fractional Gaussian noise (fGn), these two parameters are linearly related. This may be regarded as a limitation of fGn in traffic modeling from the point of view of either accurately fitting real traffic or appropriately explaining the particular multi-fractal phenomena of traffic. In this paper, we discuss recent results in traffic modeling from a view of the generalized Cauchy (GC) process. The GC process is indexed by two parameters D and H. The parameter D in the GC model is independent of H. Hence, it provides a more flexible way to describe the multi-fractal phenomena of traffic in addition to accurately modeling traffic for both short-term lags and long-term ones. (c) 2008 Elsevier B.V. All rights reserved. |
| first_indexed | 2025-11-14T18:07:52Z |
| format | Article |
| id | mmu-2749 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:07:52Z |
| publishDate | 2008 |
| publisher | ELSEVIER SCIENCE BV |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-27492011-09-13T01:38:17Z http://shdl.mmu.edu.my/2749/ Modeling network traffic using generalized Cauchy process LI, M LIM, S T Technology (General) QC Physics Processes with long-range dependence (LRD) have gained wide applications in many fields of science and technologies ranging from hydrology to network traffic. Two key properties of such processes are LRD that is characterized by the Hurst parameter H and self-similarity (SS) that is measured by the fractal dimension D. However, in the popular traffic model using fractional Gaussian noise (fGn), these two parameters are linearly related. This may be regarded as a limitation of fGn in traffic modeling from the point of view of either accurately fitting real traffic or appropriately explaining the particular multi-fractal phenomena of traffic. In this paper, we discuss recent results in traffic modeling from a view of the generalized Cauchy (GC) process. The GC process is indexed by two parameters D and H. The parameter D in the GC model is independent of H. Hence, it provides a more flexible way to describe the multi-fractal phenomena of traffic in addition to accurately modeling traffic for both short-term lags and long-term ones. (c) 2008 Elsevier B.V. All rights reserved. ELSEVIER SCIENCE BV 2008-04 Article NonPeerReviewed LI, M and LIM, S (2008) Modeling network traffic using generalized Cauchy process. Physica A: Statistical Mechanics and its Applications, 387 (11). pp. 2584-2594. ISSN 03784371 http://dx.doi.org/10.1016/j.physa.2008.01.026 doi:10.1016/j.physa.2008.01.026 doi:10.1016/j.physa.2008.01.026 |
| spellingShingle | T Technology (General) QC Physics LI, M LIM, S Modeling network traffic using generalized Cauchy process |
| title | Modeling network traffic using generalized Cauchy process |
| title_full | Modeling network traffic using generalized Cauchy process |
| title_fullStr | Modeling network traffic using generalized Cauchy process |
| title_full_unstemmed | Modeling network traffic using generalized Cauchy process |
| title_short | Modeling network traffic using generalized Cauchy process |
| title_sort | modeling network traffic using generalized cauchy process |
| topic | T Technology (General) QC Physics |
| url | http://shdl.mmu.edu.my/2749/ http://shdl.mmu.edu.my/2749/ http://shdl.mmu.edu.my/2749/ |