Wait-Freedom with Advice

TL;DR

This paper introduces a new model for understanding how failure detectors can enable wait-free solutions in distributed systems, providing a classification of tasks based on the weakest failure detectors needed.

Contribution

It proposes a novel framework for defining wait-freedom with failure detectors and characterizes tasks by their weakest failure detectors, including complex tasks like renaming.

Findings

Characterizes tasks by their weakest failure detectors.

Provides a complete classification of distributed tasks.

Includes tasks previously not well-characterized, like renaming.

Abstract

We motivate and propose a new way of thinking about failure detectors which allows us to define, quite surprisingly, what it means to solve a distributed task \emph{wait-free} \emph{using a failure detector}. In our model, the system is composed of \emph{computation} processes that obtain inputs and are supposed to output in a finite number of steps and \emph{synchronization} processes that are subject to failures and can query a failure detector. We assume that, under the condition that \emph{correct} synchronization processes take sufficiently many steps, they provide the computation processes with enough \emph{advice} to solve the given task wait-free: every computation process outputs in a finite number of its own steps, regardless of the behavior of other computation processes. Every task can thus be characterized by the \emph{weakest} failure detector that allows for solving it, and we show that every such failure detector captures a form of set agreement. We then obtain a complete classification of tasks, including ones that evaded comprehensible characterization so far, such as renaming or weak symmetry breaking.