Snap-Stabilization in Message-Passing Systems

Delaët, Sylvie; Devismes, Stéphane; Nesterenko, Mikhail; Tixeuil, Sébastien

doi:10.1007/978-3-540-92295-7_34

Cited by 11 publications

(12 citation statements)

References 29 publications

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“…Due to the great safety feature of snap-stabilization, it is now crucial to solve this open question : "What is the expressiveness of snap-stabilization in asynchronous message passing?" Following the impossibility result of [26], this question cannot hold for deterministic snap-stabilizing algorithms on systems with unbounded or unknown capacity channels. Nevertheless, the expressiveness of snap-stabilization in the asynchronous message-passing model with known bounds on link capacity is a challenging open question, in particular when considering identified networks of arbitrary topologies.…”

Section: Resultsmentioning

confidence: 99%

“…Most of the above work is designed in the locally shared memory model. Only a few papers deal with snapstabilization in message-passing systems [25,26,27]. In [25], the authors sketch a snap-stabilizing snapshot algorithm for oriented tree networks.…”

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confidence: 99%

“…In [25], the authors sketch a snap-stabilizing snapshot algorithm for oriented tree networks. The algorithms given in [26] deals with PIF and mutual exclusion in complete networks. Mohamed et al proposed a snap-stabilizing PIF algorithm for unoriented tree networks in [27].…”

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confidence: 99%

“…Again, the answer is yes. Two algorithms that are snap-stabilizing for Specification 1.2 are proposed in [12,26].…”

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confidence: 99%

“…Notice that snap-stabilizing algorithms for some dedicated problems in particular topologies already exist in the asynchronous message-passing model with known bounds on link capacity, e.g.,[25,26,27].…”

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confidence: 99%

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The expressive power of snap-stabilization

Cournier

Datta

Devismes

et al. 2016

Theoretical Computer Science

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International audienceA snap-stabilizing algorithm, regardless of the initial configuration of the system, guarantees that it always behaves according to its specification. We consider here the locally shared memory model. In this model, we propose the first snap-stabilizing Propagation of Information with Feedback (PIF) algorithm for rooted networks of arbitrary connected topology which is proven assuming the distributed unfair daemon. Then, we use the proposed PIF algorithm as a key module in designing snap-stabilizing solutions for some fundamental problems in distributed systems, such as Leader Election, Reset, Snapshot, and Termination Detection. Finally, we show that in the locally shared memory model, snap-stabilization is as expressive as self-stabilization by designing a universal transformer to provide a snap-stabilizing version of any algorithm that can be self-stabilized with the transformer of Katz and Perry (Distributed Computing, 1993). Since by definition a snap-stabilizing algorithm is also self-stabilizing, self-and snap-stabilization have the same expressiveness in the locally shared memory model

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Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

“…Again, the answer is yes. Two algorithms that are snap-stabilizing for Specification 1.2 are proposed in [12,26].…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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The expressive power of snap-stabilization

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Datta

Devismes

et al. 2016

Theoretical Computer Science

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Practically-Self-stabilizing Vector Clocks in the Absence of Execution Fairness

Salem

Schiller

2019

Networked Systems

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Vector clock algorithms are basic wait-free building blocks that facilitate causal ordering of events. As wait-free algorithms, they are guaranteed to complete their operations within a finite number of steps. Stabilizing algorithms allow the system to recover after the occurrence of transient faults, such as soft errors and arbitrary violations of the assumptions according to which the system was designed to behave. We present the first, to the best of our knowledge, stabilizing vector clock algorithm for asynchronous crash-prone message-passing systems that can recover in a wait-free manner after the occurrence of transient faults. In these settings, it is challenging to demonstrate a finite and wait-free recovery from (communication and crash failures as well as) transient faults, bound the message and storage sizes, deal with the removal of all stale information without blocking, and deal with counter overflow events (which occur at different network nodes concurrently).We present an algorithm that never violates safety in the absence of transient faults and provides bounded time recovery during fair executions that follow the last transient fault. The novelty is that in the absence of execution fairness, the algorithm guarantees a bound on the number of times in which the system might violate safety (while existing algorithms might block forever due to the presence of both transient faults and crash failures).Since vector clocks facilitate a number of elementary synchronization building blocks (without requiring remote replica synchronization) in asynchronous systems, we believe that our analytical insights are useful for the design of other systems that cannot guarantee execution fairness. Context and Motivation.Vector clocks allow reasoning about causality among events in distributed systems, for example, when constructing distributed snapshots [17]. Shapiro et al. [24] showed that vector clocks are building blocks of several conflict-free replicated data types (CRDTs). CRDTs are distributed data structures that can be shared among many replicas in asynchronous networks. All replica updates occur independently and achieve strong eventual consistency without using mechanisms for synchronization [25] or roll-back.The industrial use of CRDTs includes globally distributed databases, such as the ones of Redis, Riak, Bet365, SoundCloud, TomTom, Phoenix, and Facebook. Some of these databases have around ten million concurrent users, ten thousand messages per second, store large volumes of data, and offer very low latency. However, while both the literature and the users demonstrate that large-scale decentralized systems can benefit from the use of CRDTs in general and vector clocks in particular, the relationship between fault-tolerance and strong eventual consistency has not received sufficient attention. Providing higher robustness degrees to CRDTs is nevertheless imperative for ensuring the availability and safety of these systems.Providing robustness in the presence of unexpected failures, i.e., the ones that...

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Snap-Stabilizing PIF on Non-oriented Trees and Message Passing Model

Levé

Mohamed

Villain

2014

Lecture Notes in Computer Science

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International audienceStarting from any configuration, a snap-stabilizing protocol guarantees that the system always behaves according to its specification while a self-stabilizing protocol only guarantees that the system will behave according to its specification in a finite time. So, a snap-stabilizing protocol is a time optimal self-stabilizing protocol (because it stabilizes in 0 rounds). That property is very suitable in the case of systems that are prone to transient faults. There exist a lot of approaches of the concept of self-stabilization, but to our knowledge, snap-stabilization is the only variant of self-stabilization which has been proved power equivalent to self-stabilization in the context of the state model (a locally shared memory model) and for non anonymous systems. So the problem of the existence of snap-stabilizing solutions in the message passing model is a very crucial question from a practical point of view. In this paper, we present the first snap-stabilizing propagation of information with feedback (PIF) protocol for non-oriented trees in the message passing model. Moreover using slow and fast timers, the round complexity of our algorithm is in θ(h ×k) and θ((h ×k) + k 2), respectively, where h is the height of the tree and k is the maximal capacity of the channels. We conjecture that our algorithm is optimal

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Snap-Stabilization in Message-Passing Systems

Cited by 11 publications

References 29 publications

The expressive power of snap-stabilization

The expressive power of snap-stabilization

Practically-Self-stabilizing Vector Clocks in the Absence of Execution Fairness

Snap-Stabilizing PIF on Non-oriented Trees and Message Passing Model

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