Impact of delay classes on the data structure in IOTA

TL;DR

This paper models how different delay classes of messages affect the tip pool size in IOTA's DAG-based data structure, providing insights for better protocol control and performance optimization.

Contribution

It introduces a novel model for multiple delay classes in DAGs and applies it to IOTA 2.0, highlighting the impact of delay classes on tip pool size.

Findings

Tip pool size is strongly influenced by the dominant delay class.

The model accurately predicts tip pool size for multiple delay classes.

Adjusting message references can control tip pool size effectively.

Abstract

In distributed ledger technologies (DLTs) with a directed acyclic graph (DAG) data structure, a message-issuing node can decide where to append that message and, consequently, how to grow the DAG. This DAG data structure can typically be decomposed into two pools of messages: referenced messages and unreferenced messages (tips). The selection of the parent messages to which a node appends the messages it issues, depends on which messages it considers as tips. However, the exact time that a message enters the tip pool of a node depends on the delay of that message. In previous works, it was considered that messages have the same or similar delay; however, this generally may not be the case. We introduce the concept of classes of delays, where messages belonging to a certain class have a specific delay, and where these classes coexist in the DAG. We provide a general model that predicts the tip pool size for any finite number of different classes. This categorisation and model is applied to the first iteration of the IOTA 2.0 protocol (a.k.a. Coordicide), where two distinct classes, namely value and data messages, coexist. We show that the tip pool size depends strongly on the dominating class that is present. Finally, we provide a methodology for controlling the tip pool size by dynamically adjusting the number of references a message creates.