To design robust and reliable networks and network services, understanding the characteristics of Internet traffic becomes critical (Wikipedia 2006a). In traditional telephone networks, Poisson distributions are used, however empirical studies of measured traffic traces have led to the wide recognition of self-similarityin network traffic (Wikipedia 2006a). Self-similar Ethernet traffic exhibits dependencies over a long range of time scales, whereas telephone traffic is Poisson in it's arrival and departure processes (Wikipedia 2006b).
With many time-series if the series is averaged then the data begins to look smoother (Wikipedia 2006b). However, with self-similar data, one is confronted with traces which are spiky and bursty, even at large scales (Wikipedia 2006b). Such behaviour is caused by strong dependence in the data: large values tend to come in clusters, and clusters of clusters, etc (Wikipedia 2006b). This can have far-reaching consequences for network performance (Wikipedia 2006b). Ethernet, WWW, SS7, TCP, FTP, TELNET, and VBR video (digitised video of the type that is transmitted over ATM networks) traffic is self-similar (Wikipedia 2006b).
Self-similarity in packetised data networks can be caused by the distribution of file sizes, human interactions and/or Ethernet dynamics (Wikipedia 2006b). Self-similar and long-range dependentcharacteristics in computer networks present a fundamentally different set of problems to people doing analysis and/or design of networks, and many of the previous assumptions upon which systems have been built are no longer valid in the presence of self-similarity (Wikipedia 2006b).
The following list contains examples of non-Poisson traffic.Examples:
Exercise: If an individual uses a dial-up modem from a home PC, to download a PDF document from the internet, is this traffic considered Poisson or non- Poisson? Answer.
References:
Wikipedia. "Teletraffic engineering", Wikimedia Foundation Inc, http://en.wikipedia.org/wiki/Teletraffic_engineering, Last accessed 9 February 2006.Wikipedia. "Long-tail traffic", Wikimedia Foundation Inc, http://en.wikipedia.org/wiki/Long-tail_traffic, Last accessed 10 February 2006.
Brandon Hodgson




