Proportionally Fair approach for Tor's Circuits Scheduling

by   Lamiaa Basyoni, et al.

The number of users adopting Tor to protect their online privacy is increasing rapidly. With a limited number of volunteered relays in the network, the number of clients' connections sharing the same relays is increasing to the extent that it is starting to affect the performance. Recently, Tor's resource allocation among circuits has been studied as one cause of poor Tor network performance. In this paper, we propose two scheduling approaches that guarantee proportional fairness between circuits that are sharing the same connection. In our evaluation, we show that the average-rate-base scheduler allocates Tor's resources in an optimal fair scheme, increasing the total throughput achieved by Tor's relays. However, our second proposed approach, an optimization-based scheduler, maintains acceptable fairness while reducing the latency experienced by Tor's clients.



There are no comments yet.


page 1

page 2

page 3

page 4


Selective Fair Scheduling over Fading Channels

Imposing fairness in resource allocation incurs a loss of system through...

Online Task Scheduling for Fog Computing with Multi-Resource Fairness

In fog computing systems, one key challenge is online task scheduling, i...

Performance Evaluation of Scheduling in 5G-mmWave Networks under Human Blockage

The millimetre-wave spectrum provisions enormous enhancement to the achi...

QAOA-based Fair Sampling on NISQ Devices

We study the status of fair sampling on Noisy Intermediate Scale Quantum...

A New Fairness Model based on User's Objective for Multi-user Multi-processor Online Scheduling

Resources of a multi-user system in multi-processor online scheduling ar...

Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP

Resource allocation problems in many computer systems can be formulated ...

Optimal Sharing and and Fair Cost Allocation of Community Energy Storage

This paper studies an optimal energy storage (ES) sharing model which is...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.