The Accuracy of Tree-based Counting in Dynamic Networks

TL;DR

This paper analyzes the accuracy of tree-based network size estimation protocols under churn using a Markov model, validated by simulations across various network conditions.

Contribution

It introduces a Markov model for analyzing tree-based protocols under churn, providing new insights into their performance and accuracy in dynamic networks.

Findings

Model accurately predicts node distribution and subnetwork sizes under churn.

Simulation results validate the analytical model across different network scenarios.

Tree-based protocols maintain reasonable accuracy despite network dynamics.

Abstract

Tree-based protocols are ubiquitous in distributed systems. They are flexible, they perform generally well, and, in static conditions, their analysis is mostly simple. Under churn, however, node joins and failures can have complex global effects on the tree overlays, making analysis surprisingly subtle. To our knowledge, few prior analytic results for performance estimation of tree based protocols under churn are currently known. We study a simple Bellman-Ford-like protocol which performs network size estimation over a tree-shaped overlay. A continuous time Markov model is constructed which allows key protocol characteristics to be estimated, including the expected number of nodes at a given (perceived) distance to the root and, for each such node, the expected (perceived) size of the subnetwork rooted at that node. We validate the model by simulation, using a range of network sizes, node degrees, and churn-to-protocol rates, with convincing results.