Practically Self-stabilizing Paxos Replicated State-Machine

Blanchard, Peva; Beauquier, Joffroy; Delaët, Sylvie

doi:10.1007/978-3-319-09581-3_8

Cited by 30 publications

(49 citation statements)

References 17 publications

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“…By contrast, stabilization can often be achieved by only processes in the vicinity of the affected processes [7], [14]. Compared with the work in [4] which assumes the counter size to be equal to the size of integers (32/64 bit in most systems), our approach has the potential to reduce the size of the counters. For example, the analysis from Section A, shows a bound of 780 is sufficient.…”

Section: Discussion and Related Workmentioning

confidence: 99%

Preserving Stabilization While Practically Bounding State Space

Valapil

Kulkarni²

2017

2017 13th European Dependable Computing Conference (EDCC)

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Abstract-Stabilization is a key dependability property for dealing with unanticipated transient faults, as it guarantees that even in the presence of such faults, the system will recover to states where it satisfies its specification. One of the desirable attributes of stabilization is the use of bounded space for each variable.In this paper, we present an algorithm that transforms a stabilizing program that uses variables with unbounded domain into a stabilizing program that uses bounded variables and (practically bounded) physical time. While non-stabilizing programs (that do not handle transient faults) can deal with unbounded variables by assigning large enough but bounded space, stabilizing programs -that need to deal with arbitrary transient faults-cannot do the same since a transient fault may corrupt the variable to its maximum value.We show that our transformation algorithm is applicable to several problems including logical clocks, vector clocks, mutual exclusion, leader election, diffusing computations, Paxos based consensus, and so on. Moreover, our approach can also be used to bound counters used in an earlier work by Katz and Perry for adding stabilization to a non-stabilizing program. By combining our algorithm with that earlier work by Katz and Perry, it would be possible to provide stabilization for a rich class of problems, by assigning large enough but bounded space for variables.

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Section: Discussion and Related Workmentioning

confidence: 99%

Preserving Stabilization While Practically Bounding State Space

Valapil

Kulkarni²

2017

2017 13th European Dependable Computing Conference (EDCC)

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“…A recent research line on (practically) self-stabilizing versions of replicated state machines [1,6,9,10] obtains self-stabilizing replicated state machines in shared memory as well as synchronized and asynchronous message passing systems.…”

Section: Contributionsmentioning

confidence: 99%

“…In [6] a self-stabilizing version of Paxos was developed that led to a selfstabilizing consensus-based SMR implementation. To this end, a labeling scheme extending the one of [1] to allow multiple writers.…”

Section: Contributionsmentioning

confidence: 99%

“…is an alternating sequence of system configurations c x and steps a x , such that each configuration c x+1 , except the initial configuration c 0 , is obtained from the preceding configuration c x by the execution of the step a x . A practically infinite execution [6] is an execution with many steps (and iterations), where "many" is defined to be proportional to the time it takes to execute a step and the life-span time of a system. We define the system's task by a set of executions called legal executions (LE) in which the task's requirements hold, we use the term safe configuration for any configuration in LE.…”

Section: System Settingsmentioning

confidence: 99%

“…Once the heartbeat counter value of a processor q reaches W, the failure detector of p considers q as inactive. In other words, the failure detector at p considers processor q to be active, if and only if the heartbeat associated with q is strictly less than W. This is essentially the failure detector implementation mentioned in [6]. Note that for the correctness of our VS algorithm, we require a weaker failure detector.…”

Section: Preliminariesmentioning

confidence: 99%

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Self-stabilizing Virtual Synchrony

Georgiou

Marcoullis

Schiller

2015

Lecture Notes in Computer Science

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Citation for the published paper: Dolev, S. ; Georgiou, C. ; Marcoullis, I. et al. (2015) Abstract. Virtual synchrony (VS) is an important abstraction that is proven to be extremely useful when implemented over asynchronous, typically large, message-passing distributed systems. Fault tolerant design is critical for the success of such implementations since large distributed systems can be highly available as long as they do not depend on the full operational status of every system participant. Self-stabilizing systems can tolerate transient faults that drive the system to an arbitrary unpredictable configuration. Such systems automatically regain consistency from any such configuration, and then produce the desired system behavior ensuring it for practically infinite number of successive steps, e.g., 2 64 steps. We present a new multi-purpose self-stabilizing counter algorithm establishing an efficient practically unbounded counter, that can directly yield a self-stabilizing Multiple-Writer Multiple-Reader (MWMR) register emulation. We use our counter algorithm, together with a selfstabilizing group membership and a self-stabilizing multicast service to devise the first practically stabilizing VS algorithm and a self-stabilizing VS-based emulation of state machine replication (SMR). As we base the SMR implementation on VS, rather than consensus, the system progresses in more extreme asynchronous settings in relation to consensusbased SMR.

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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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Practically Self-stabilizing Paxos Replicated State-Machine

Cited by 30 publications

References 17 publications

Preserving Stabilization While Practically Bounding State Space

Preserving Stabilization While Practically Bounding State Space

Self-stabilizing Virtual Synchrony

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

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