Causality is Graphically Simple

TL;DR

This paper introduces a graphical notation for understanding causality in distributed systems, explaining classic mechanisms and recent advances to intuitively interpret event causality relations.

Contribution

It presents a new graphical notation that simplifies the interpretation of causality relations in distributed systems, integrating classic and recent causality tracking methods.

Findings

Graphical notation enhances understanding of causality

Causality tracking mechanisms are systematically explained

Recent developments in causality analysis are covered

Abstract

Events in distributed systems include sending or receiving messages, or changing some state in a node. Not all events are related, but some events can cause and influence how other, later events, occur. For instance, a reply to a received mail message is influenced by that message, and maybe by other prior messages also received. This article brings an introduction to classic causality tracking mechanisms and covers some more recent developments. The presentation is supported by a new graphical notation that allows an intuitive interpretation of the causality relations described.