Small-time scaling behaviors of Internet backbone traffic: an empirical study
- 12 May 2003
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 3, 1826-1836
- https://doi.org/10.1109/infcom.2003.1209205
Abstract
Conference PaperWe study the small-time (sub-seconds) scaling behaviors of Internet backbone traffic, based on traces collected from OC3/12/48 links in a tier-1 ISP. We observe that for a majority of these traces, the (second-order) scaling exponents at small time scales (1ms - 100ms) are fairly close to 0.5, indicating that traffic fluctuations at these time scales are (nearly) uncorrelated. In addition, the traces manifest mostly monofractal behaviors at small time scales. The objective of the paper is to understand the potential causes or factors that influence the small-time scalings of Internet backbone traffic via empirical data analysis. We analyze the traffic composition of the traces along two dimensions â flow size and flow density. Our study uncovers dense flows (i.e., flows with bursts of densely clustered packets) as the correlation-causing factor in small time scales, and reveals that the traffic composition in terms of proportions of dense vs. sparse flows plays a major role in influecing the small-time scalings of aggregate trafficKeywords
This publication has 18 references indexed in Scilit:
- Multiscale nature of network trafficIEEE Signal Processing Magazine, 2002
- Passive estimation of TCP round-trip timesACM SIGCOMM Computer Communication Review, 2002
- A non-instrusive, wavelet-based approach to detecting network performance problemsPublished by Association for Computing Machinery (ACM) ,2001
- Connection-level analysis and modeling of network trafficPublished by Association for Computing Machinery (ACM) ,2001
- Dynamics of IP trafficPublished by Association for Computing Machinery (ACM) ,1999
- The concept of relevant time scales and its application to queuing analysis of self-similar traffic (or is Hurst naughty or nice?)Published by Association for Computing Machinery (ACM) ,1998
- Wavelet analysis of long-range-dependent trafficIEEE Transactions on Information Theory, 1998
- On the relevance of long-range dependence in network trafficACM SIGCOMM Computer Communication Review, 1996
- Self-similarity through high-variabilityACM SIGCOMM Computer Communication Review, 1995
- Fractal estimation from noisy data via discrete fractional Gaussian noise (DFGN) and the Haar basisIEEE Transactions on Signal Processing, 1993