DiProber: Using Dual Probing to Estimate Tor Relay Capacities in Underloaded Networks

TL;DR

DiProber introduces a dual-probing method with maximum likelihood estimation to improve relay capacity estimates in underloaded Tor networks, enhancing load balancing and utilization.

Contribution

The paper presents a novel dual-probing measurement scheme and estimation algorithm that outperform existing methods in low-demand scenarios.

Findings

Improved accuracy of relay capacity estimates in underloaded networks

Enhanced load balancing and network utilization

Better fairness in relay selection

Abstract

Tor is the most popular anonymous communication network. It has millions of daily users seeking privacy while browsing the internet. It has thousands of relays to route and anonymize the source and destinations of the users packets. To create a path, Tor authorities generate a probability distribution over relays based on the estimates of the capacities of the relays. An incoming user will then sample this probability distribution and choose three relays for their paths. The estimates are based on the bandwidths of observation probes the authority assigns to each relay in the network. Thus, in order to achieve better load balancing between users, accurate estimates are necessary. Unfortunately, the currently implemented estimation algorithm generate inaccurate estimates causing the network to be under utilized and its capacities unfairly distributed between the users paths. We propose DiProber, a new relay capacity estimation algorithm. The algorithm proposes a new measurement scheme in Tor consisting of two probes per relay and uses maximum likelihood to estimate their capacities. We show that the new technique works better in the case of under-utilized networks where users tend to have very low demand on the Tor network.