The extended alternating fractal renewal process for modeling traffic in high-speed communication networks

@article{Yang2001TheEA,
  title={The extended alternating fractal renewal process for modeling traffic in high-speed communication networks},
  author={Xueshi Yang and Athina P. Petropulu},
  journal={IEEE Trans. Signal Processing},
  year={2001},
  volume={49},
  pages={1349-1363}
}
Extensive studies indicate that traffic in high-speed communication networks exhibits long-range dependence (LRD) and impulsiveness, which pose new challenges in network engineering. While many models have appeared for capturing the traffic LRD, fewer models exist that account for impulsiveness as well as LRD. One of the few existing constructive models for network traffic is the celebrated on/off model or the alternating fractal renewal process (AFRP). However, although the AFRP results in… CONTINUE READING

Figures and Topics from this paper.

Similar Papers

Citations

Publications citing this paper.
SHOWING 1-10 OF 22 CITATIONS

Notice of RetractionOn convergence of aggregated traffic to long-range dependent α-stable processes

  • 2010 3rd International Conference on Computer Science and Information Technology
  • 2010
VIEW 8 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Rate-limited EAFRP-a new improved model for high-speed network traffic

  • IEEE Transactions on Signal Processing
  • 2005
VIEW 12 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Performance Analysis of Spectrum Sensing With Multiple Primary Users

  • IEEE Transactions on Vehicular Technology
  • 2012
VIEW 1 EXCERPT
CITES METHODS

Spectrum Sensing Optimisation for Dynamic Primary User Signal

  • IEEE Transactions on Communications
  • 2012
VIEW 1 EXCERPT
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 35 REFERENCES

Fractal renewal processes generate 1/f noise.

  • Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
  • 1993
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Forecasting network traffic using FARIMA models with heavy tailed innovations

  • 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)
  • 2000
VIEW 1 EXCERPT