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Stabilizing Consensus is Impossible in Lossy Iterated Immediate Snapshot Models

Stephan Felber, Hugo Rincon Galeana

TL;DR

This paper introduces the novel Delayed Lossy-Link (DLL) model, and the Lossy Iterated Immediate Snapshot Model (LIIS), for which it is shown that stabilizing consensus is impossible even when f=1, and shows that even in a model with very strong connectivity, a single omission fault per layer effectively disables stabilizing consensus.

Abstract

A substantial portion of distributed computing research is dedicated to terminating problems like consensus and similar agreement problems. However, non-terminating problems have been intensively studied in the context of self-stabilizing distributed algorithms, where processes may start from arbitrary initial states and can tolerate arbitrary transient faults. In between lie stabilizing problems, where the processes start from a well-defined initial state, but do not need to decide irrevocably and are allowed to change their decision finitely often until a stable decision is eventually reached. In this paper, we introduce the novel Delayed Lossy-Link (DLL) model, and the Lossy Iterated Immediate Snapshot Model (LIIS), for which we show stabilizing consensus to be impossible. The DLL model is introduced as a variant of the well-known Lossy-Link model, which admits silence periods of arbitrary but finite length. The LIIS model is a variant of the Iterated Immediate Snapshot (IIS), model which admits finite length periods of at most $f$ omission faults per layer. In particular, we show that stabilizing consensus is impossible even when $f=1$. Our results show that even in a model with very strong connectivity, namely, the Iterated Immediate Snapshot (IIS) model, a single omission fault per layer effectively disables stabilizing consensus. Furthermore, since the DLL model always has a perpetual broadcaster, the mere existence of a perpetual broadcaster, even in a crash-free setting, is not sufficient for solving stabilizing consensus, negatively answering the open question posed by Charron-Bost and Moran.

Stabilizing Consensus is Impossible in Lossy Iterated Immediate Snapshot Models

TL;DR

This paper introduces the novel Delayed Lossy-Link (DLL) model, and the Lossy Iterated Immediate Snapshot Model (LIIS), for which it is shown that stabilizing consensus is impossible even when f=1, and shows that even in a model with very strong connectivity, a single omission fault per layer effectively disables stabilizing consensus.

Abstract

A substantial portion of distributed computing research is dedicated to terminating problems like consensus and similar agreement problems. However, non-terminating problems have been intensively studied in the context of self-stabilizing distributed algorithms, where processes may start from arbitrary initial states and can tolerate arbitrary transient faults. In between lie stabilizing problems, where the processes start from a well-defined initial state, but do not need to decide irrevocably and are allowed to change their decision finitely often until a stable decision is eventually reached. In this paper, we introduce the novel Delayed Lossy-Link (DLL) model, and the Lossy Iterated Immediate Snapshot Model (LIIS), for which we show stabilizing consensus to be impossible. The DLL model is introduced as a variant of the well-known Lossy-Link model, which admits silence periods of arbitrary but finite length. The LIIS model is a variant of the Iterated Immediate Snapshot (IIS), model which admits finite length periods of at most omission faults per layer. In particular, we show that stabilizing consensus is impossible even when . Our results show that even in a model with very strong connectivity, namely, the Iterated Immediate Snapshot (IIS) model, a single omission fault per layer effectively disables stabilizing consensus. Furthermore, since the DLL model always has a perpetual broadcaster, the mere existence of a perpetual broadcaster, even in a crash-free setting, is not sufficient for solving stabilizing consensus, negatively answering the open question posed by Charron-Bost and Moran.
Paper Structure (10 sections, 11 theorems, 6 equations)

This paper contains 10 sections, 11 theorems, 6 equations.

Key Result

Theorem 1

Asymptotic consensus, where processes are only required to agree in the limit, is solvable in the $\texttt{DLL}$.

Theorems & Definitions (21)

  • Theorem 1: $\texttt{DLL}$ allows Asymptotic consensus
  • Definition 2: Stabilizing Task Solvability
  • Definition 3: Consensus Task
  • Definition 4: Lossy-Link message adversary
  • Definition 5: Bounded-Delay Lossy-Link message adversary
  • Definition 6: Delayed Lossy-Link Message Adversary
  • Definition 7: Conflicted prefix
  • Definition 8: Patient prefix
  • Lemma 9: Patience Lemma
  • Definition 10: Patience
  • ...and 11 more