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Traffic measurement and analysis
RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.ORCID-id: 0000-0002-8102-5773
1999 (Engelska)Rapport (Övrigt vetenskapligt)
Abstract [en]

Measurement and analysis of real traffic is important to gain knowledge about the characteristics of the traffic. Without measurement, it is impossible to build realistic traffic models. It is recent that data traffic was found to have self-similar properties. In this thesis work traffic captured on the network at SICS and on the Supernet, is shown to have this fractal-like behaviour. The traffic is also examined with respect to which protocols and packet sizes are present and in what proportions. In the SICS trace most packets are small, TCP is shown to be the predominant transport protocol and NNTP the most common application. In contrast to this, large UDP packets sent between not well-known ports dominates the Supernet traffic. Finally, characteristics of the client side of the WWW traffic are examined more closely. In order to extract useful information from the packet trace, web browsers use of TCP and HTTP is investigated including new features in HTTP/1.1 such as persistent connections and pipelining. Empirical probability distributions are derived describing session lengths, time between user clicks and the amount of data transferred due to a single user click. These probability distributions make up a simple model of WWW-sessions.

Ort, förlag, år, upplaga, sidor
Kista, Sweden: Swedish Institute of Computer Science , 1999, 1. , 52 s.
Serie
SICS Technical Report, ISSN 1100-3154 ; T99:05
Nyckelord [en]
Traffic measurement, self-similarity
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:ri:diva-21973OAI: oai:DiVA.org:ri-21973DiVA: diva2:1041515
Tillgänglig från: 2016-10-31 Skapad: 2016-10-31 Senast uppdaterad: 2017-10-17Bibliografiskt granskad

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Abrahamsson, Henrik
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Decisions, Networks and Analytics lab
Data- och informationsvetenskap

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