Introduction to Distributed Self-Stabilizing Algorithms

Altisen, Karine; Devismes, Stéphane; Dubois, Swan; Petit, Franck

doi:10.1007/978-3-031-02013-1

Cited by 32 publications

(25 citation statements)

References 100 publications

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“…Indeed, several robots acted simultaneously in our demos. A similar concept regarding activation is known as a locally central daemon in theoretical distributed algorithms [21]. Throughout the article, we assume that each path π i starts from s i and ends at g i to focus on analyses related to schedules.…”

Section: B Rationale and Remarksmentioning

confidence: 99%

Offline Time-Independent Multiagent Path Planning

et al. 2023

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This study examines a novel planning problem for multiple agents that cannot share holding resources, named Offline Time-Independent Multiagent Path Planning (OTIMAPP). Given a graph and a set of start-goal pairs, the problem to be addressed is assigning a path to each agent, such that every agent eventually reaches its destination without blocking others, regardless of when each agent starts and finishes each own action. This motivation stems from timing uncertainties, including the reality gaps between planning and robot execution. In contrast to conventional solution, concepts of multirobot path planning that rely on timings, once OTIMAPP solutions are obtained, they can be executed without any synchronization between robot actions. Moreover, there is a theoretical guarantee that all robots eventually reach their destinations, provided they avoid interrobot collisions. This study attempts to establish OTIMAPP both theoretically and practically. Specifically, we present a formalization of the problem, solution conditions based on a categorization of deadlocks, computational complexities showing that OTIMAPP is computationally intractable, practical relaxation of the solution concept, two algorithms to solve OTIMAPP based on multiagent pathfinding algorithms, empirical results showing large OTIMAPP instances can be solved to some extent, as well as robot demonstrations of asynchronous OTIMAPP execution.

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Section: B Rationale and Remarksmentioning

confidence: 99%

Offline Time-Independent Multiagent Path Planning

et al. 2023

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“…Since the occurrence of these failures can be arbitrarily combined, we assume these transient-faults can alter the system state in unpredictable ways. In particular, when modeling the system, Dijkstra [15] assumes that these violations bring the system to an arbitrary state from which a self-stabilizing system should recover [3,16]. I.e., Dijkstra requires (i) recovery after the last occurrence of a transient-fault and (ii) once the system has recovered, it must never violate the task requirements.…”

Section: Self-stabilizationmentioning

confidence: 99%

Self-stabilizing Byzantine Fault-Tolerant Repeated Reliable Broadcast

Duvignau

Raynal

Schiller

2022

Lecture Notes in Computer Science

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Consensus, abstracting a myriad of problems in which processes have to agree on a single value, is one of the most celebrated problems of fault-tolerant distributed computing. Consensus applications include fundamental services for the environments of the Cloud and Blockchain, and in such challenging environments, malicious behaviors are often modeled as adversarial Byzantine faults.At OPODIS 2010, Mostéfaoui and Raynal (in short MR) presented a Byzantinetolerant solution to consensus in which the decided value cannot be a value proposed only by Byzantine processes. MR has optimal resilience coping with up to t < n/3 Byzantine nodes over n processes. MR provides this multivalued consensus object (which accepts proposals taken from a finite set of values) assuming the availability of a single Binary consensus object (which accepts proposals taken from the set {0, 1}).This work, which focuses on multivalued consensus, aims at the design of an even more robust solution than MR. Our proposal expands MR's fault-model with self-stabilization, a vigorous notion of fault-tolerance. In addition to tolerating Byzantine, self-stabilizing systems can automatically recover after the occurrence of arbitrary transient-faults. These faults represent any violation of the assumptions according to which the system was designed to operate (provided that the algorithm code remains intact).To the best of our knowledge, we propose the first self-stabilizing solution for intrusion-tolerant multivalued consensus for asynchronous message-passing systems prone to Byzantine failures. Our solution has a O(t) stabilization time from arbitrary transient faults.

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“…I.e., there could be any finite number of transient faults before the last one occurs, which may leave the system in an arbitrary state. Moreover, recovery from an arbitrary system state is demonstrated once all transient faults cease to happen, see [4,15] for details. Memory constraints.…”

Section: Self-stabilizationmentioning

confidence: 99%

“…We refer to these violations and deviations as arbitrary transient-faults and assume that they can corrupt the system state arbitrarily (while keeping the program code intact). Our model assumes that the last arbitrary transient fault occurs before the system execution starts [4,15]. Also, it leaves the system to start in an arbitrary state.…”

Section: Arbitrary Transient-faultsmentioning

confidence: 99%

Loosely-self-stabilizing Byzantine-Tolerant Binary Consensus for Signature-Free Message-Passing Systems

et al. 2021

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Numerous distributed applications, such as cloud computing and distributed ledgers, necessitate the system to invoke asynchronous consensus objects an unbounded number of times, where the completion of one consensus instance is followed by the invocation of another. With only a constant number of objects available, object reuse becomes vital.We investigate the challenge of object recycling in the presence of Byzantine processes, which can deviate from the algorithm code in any manner. Our solution must also be self-stabilizing, as it is a powerful notion of fault tolerance. Self-stabilizing systems can recover automatically after the occurrence of arbitrary transient-faults, in addition to tolerating communication and (Byzantine or crash) process failures, provided the algorithm code remains intact.We provide a recycling mechanism for asynchronous objects that enables their reuse once their task has ended, and all non-faulty processes have retrieved the decided values. This mechanism relies on synchrony assumptions and builds on a new self-stabilizing Byzantine-tolerant synchronous multivalued consensus algorithm, along with a novel composition of existing techniques.

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Introduction to Distributed Self-Stabilizing Algorithms

Cited by 32 publications

References 100 publications

Offline Time-Independent Multiagent Path Planning

Offline Time-Independent Multiagent Path Planning

Self-stabilizing Byzantine Fault-Tolerant Repeated Reliable Broadcast

Loosely-self-stabilizing Byzantine-Tolerant Binary Consensus for Signature-Free Message-Passing Systems

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