Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. EPFL thesis
  4. Network Neutrality Inference using Network Tomography
 
doctoral thesis

Network Neutrality Inference using Network Tomography

Mara, Ovidiu Sebastian  
2018

Our work studies network neutrality, a property of communication networks which means that they treat all traffic the same, regardless of application, content provider or communication protocol. This is an important problem, because sometimes users suspect their ISPs of violating network neutrality, but apply inaccurate methods to check their suspicions, reaching incorrect conclusions.

Prior non-neutrality detection methods either provide only detection, but lack localization capabilities; or also perform localization, but assume perfect measurements. For the latter, we show that, in practice, the measurement process can severely impact the results.

We present a method that performs both non-neutrality detection and localization, using only end-to-end measurements, and assuming an imperfect measurement process. We identify the sources of measurement error that may affect our method, we address them, and evaluate the method extensively with simulations, emulations and experiments on the Internet. We also use our method in two studies, investigating suspicions that a set of ISPs prioritize speed-test traffic, or differentiate against BitTorrent traffic; despite circumstancial evidence that they do, we obtain reliable evidence to the contrary. Finally, we present the network emulator that we built to evaluate our method, hoping that it will be a useful tool in future research.

We conclude that it is feasible to detect and localize network neutrality violations based solely on end-to-end measurements, without assuming a perfect measurement process; and that it is important that reasoning about network neutrality is based on reliable evidence of network behavior.

  • Files
  • Details
  • Metrics
Type
doctoral thesis
DOI
10.5075/epfl-thesis-8076
Author(s)
Mara, Ovidiu Sebastian  
Advisors
Argyraki, Aikaterini  
Jury

Prof. Matthias Grossglauser (président) ; Prof. Aikaterini Argyraki (directeur de thèse) ; Prof. Patrick Thiran, Prof. Constantine Dovrolis, Prof. Krishna Gummadi (rapporteurs)

Date Issued

2018

Publisher

EPFL

Publisher place

Lausanne

Public defense year

2018-03-21

Thesis number

8076

Total of pages

125

Subjects

network neutrality

•

network tomography

•

congestion

EPFL units
NAL  
Faculty
IC  
School
IINFCOM  
Doctoral School
EDIC  
Available on Infoscience
March 15, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/145571
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés