Paper Info
Title
Experience in measuring backbone traffic variability: models, metrics, measurements and meaning
Abstract
Abstract—Understanding the variability of Internet traffic in backbone networks is essential to better plan and manage existing networks, as well as to design next generation networks. However, most traffic analyses that might be used to approach this problem are based on detailed packet or flo w level measurements, which are usually not available throughout a large network. As a result there is a poor understanding of backbone traffic variability, and its impact on network operations (e.g. on capacity planning or traffic engineering). This paper introduces a metric for measuring backbone traffic variability that is grounded on simple but powerful traffic theory. What sets this metric apart, however, is that we present a method for making practical measurements of the metric using widely available SNMP traffic measurements. Furthermore, we use a novel method to overcome the major limitation of SNMP measurements ‐ that they only provide link statistics. The method, based on a “gravity model”, derives an approximate traffic matrix from the SNMP data. In addition to simulations, we use more than 1 year’s worth of SNMP data from an operational IP network of about 1000 nodes to test our methods. We also delve into the degree and sources of variability in real backbone traffic, providing insight into the true nature of traffic variability. Despite a significant amount of research addressing Internet traffic models [1], [2], [3], [4], there is not yet widespread agreement about the characteristics of backbone Internet traffic. This problem is exacerbated by exaggerated reports on Internet traffic growth and variability [5], [6], by the challenges associated with Internet traffic measurements [7], and a lack of understanding of the applicability of results such as the discovery of self-similarity in traffic [1], [2], [3]. For instance, in [5], dire claims are made on the basis of the notion that large volumes of traffic slosh around the Internet in a highly irregular way. Obtaining the data necessary to develop an accurate and
Year
DOI
Venue
2002
10.1145/637201.637213
Internet Measurement Workshop
Keywords
Field
DocType
internet traffic,traffic engineering,snmp data,powerful traffic theory,traffic variability,available snmp traffic measurement,traffic analysis,real backbone traffic,approximate traffic matrix,backbone traffic variability,gravity model,wavelets,next generation network,scaling
Traffic generation model,Three-phase traffic theory,Computer science,Internet traffic engineering,Floating car data,Computer network,Traffic shaping,Network traffic control,Network traffic simulation,Traffic engineering,Distributed computing
Conference
ISBN
Citations 
PageRank 
1-58113-603-X
92
9.37
References 
Authors
8
6
Name
Order
Citations
PageRank
Matthew Roughan11638148.27
Albert G. Greenberg25970676.74
Charles Kalmanek319724.24
Michael Rumsewicz49210.04
Jennifer Yates579064.51
Yin Zhang63492281.04