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University of Illinois at Urbana-Champaign

High-fidelity simulation of load balancing methods in Tor

Abstract

dc:description

We evaluate the effectiveness of two novel performance improving algorithms for Tor using the Shadow simulation framework. The first is Tightrope, a path selection algorithm for improving the load balancing of Tor circuits across the Tor network. The second is using the maximum likelihood estimation (MLE) scheme to accurately estimate the true capacity of relay capacities with minimal prior knowledge. For both algorithms, we presented the technical implementation details and the experiment setup. In Tightrope's simulation results, we found that the new path selection method is effective in improving the overall throughput of the network. In MLE's simulation results, we verified its estimation accuracy under different settings.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Electrical & Computer Engr
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cheng, Chin-Yu
Contributors dc:contributor
  • Borisov, Nikita

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • Copyright 2020 Chin-Yu Cheng
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/108201
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/108201

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Cheng, Chin-Yu. High-fidelity simulation of load balancing methods in Tor. Thesis thesis, University of Illinois at Urbana-Champaign, 2020. http://hdl.handle.net/2142/108201