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On the distribution of traffic volumes in the internet and its implications
conference contribution
posted on 2023-06-09, 16:07 authored by Mohammed Alasmar, George ParisisGeorge Parisis, Richard Clegg, Nickolay ZakhleniukGetting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an equally important but less studied problem. We study a large number of traffic traces from many different networks including academic, commercial and residential networks using state-of-the-art sta- tistical techniques. We show that the log-normal distribution is a better fit than the Gaussian distribution commonly claimed in the literature. We also investigate a second heavy-tailed distribution (the Weibull) and show that its performance is better than Gaussian but worse than log-normal. We examine anomalous traces which are a poor fit for all distributions tried and show that this is often due to traffic outages or links that hit maximum capacity. We demonstrate the utility of the log-normal distribution in two contexts: predicting the proportion of time traffic will exceed a given level (for service level agreement or link capacity estimation) and predicting 95th percentile pricing. We also show the log-normal distribution is a better predictor than Gaussian or Weibull distributions.
History
Publication status
- Published
File Version
- Accepted version
Journal
IEEE INFOCOM 2019 - IEEE conference on computer communicationsISSN
2641-9874Publisher
IEEEExternal DOI
Page range
955-963Event name
The 38th IEEE International Conference on Computer Communications (INFOCOM 2019)Event location
Paris, FranceEvent type
conferenceEvent date
29th April-2nd May 2019Place of publication
Piscataway, New JerseyISBN
9781728105154Department affiliated with
- Informatics Publications
Research groups affiliated with
- Foundations of Software Systems Publications
Notes
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksFull text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2018-12-03First Open Access (FOA) Date
2019-01-25First Compliant Deposit (FCD) Date
2018-11-30Usage metrics
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