Implementing Snapshot Objects on Top of Crash-Prone Asynchronous Message-Passing Systems

Abstract

Distributed snapshots, as introduced by Chandy and Lamport in the context of asynchronous failure-free message-passing distributed systems, are consistent global states in which the observed distributed application might have passed through. It appears that two such distributed snapshots cannot necessarily be compared (in the sense of determining which one of them is the "first"). Differently, snapshots introduced in asynchronous crash-prone read/write distributed systems are totally ordered, which greatly simplify their use by upper layer applications.In order to benefit from shared memory snapshot objects, it is possible to simulate a read/write shared memory on top of an asynchronous crash-prone message-passing system, and build then snapshot objects on top of it. This algorithm stacking is costly in both time and messages. To circumvent this drawback, this paper presents algorithms building snapshot objects directly on top of asynchronous crash-prone message-passing system. "Directly" means here "without building an intermediate layer such as a read/write shared memory". To the authors knowledge, the proposed algorithms are the first providing such constructions. Interestingly enough, these algorithms are efficient and relatively simple.

Self-Stabilizing Snapshot Objects for Asynchronous Failure-Prone Networked Systems

“…We also consider an input parameter, δ. For the case of δ = 0, our self-stabilizing algorithm guarantees an always-termination behavior in a way the resembles the non-self-stabilizing algorithm by Delporte-Gallet et al [12] that blocks all write operation upon the invocation of any snapshot operation at the cost of O(n 2 ) messages. For the case of δ > 0, our solution aims at using O(n) messages per snapshot operation while monitoring the number of concurrent write operations.…”

“…The receivers of this message reply. For this request-reply behavior, the quorum-based communication functionality guarantees the following: (a) at least a quorum of nodes receive, deliver and acknowledge every message, (b) a (non-failing) sending node receives at least a majority of these replies or fulfil another return condition, e.g., arrival of a special message, and (c) immediately before returning from the quorum access, the sending-side of this service clears its state from information related Algorithm 1: The non-self-stabilizing and non-blocking algorithm by Delporte-Gallet et al [12] that emulates snapshot object; code for p i 2 local variables initialization (optional in the context of self-stabilization): 3 ssn := 0; ts := 0; /* snapshout, resp., write operation indices */ 4 reg := [⊥, . .…”

“…The algorithms we propose in the present work follow the non-stacking approach of Delporte-Gallet and they have the same communication costs for write and snapshot operations. Moreover, they tolerate any failure (in any communication or operation invocation pattern) that [12] can. Furthermore, our algorithms deal with transient faults by periodically removing stale information.…”

“…2. Our second contribution offers a self-stabilizing all-operation always-terminating variation of the snapshot-only always-terminating algorithm presented by Delporte-Gallet et al [12]. Our algorithm can: (i) recover from of transient faults, and (ii) both write and snapshot operations always terminate (regardless of the invocation patterns of any operation).…”

“…We state our system settings in Section 2. We review the non-self-stabilizing solutions by Delporte-Gallet et al [12] in Section 3. Our self-stabilizing non-blocking and always-terminating algorithms are proposed in Sections 4 and 5, respectively; they consider unbounded counters.…”