Self-stabilizing Virtual Synchrony

Georgiou, Chryssis; Marcoullis, Ioannis; Schiller, Elad Michael

doi:10.1007/978-3-319-21741-3_17

Cited by 11 publications

(43 citation statements)

References 16 publications

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“…These algorithms are derived by combining our reconfiguration scheme and joining mechanism with the corresponding self-stabilizing algorithms developed for static membership systems in [11].…”

Section: Applicationsmentioning

confidence: 99%

“…In this scheme, configuration members are the ones that run the labeling algorithm and maintain a globally maximal label and counter. The labeling and counter increment algorithms consider every new configuration as a new instance of the corresponding algorithms of [11]. To this end, Algorithm 4.1 is a wrapper of the self-stabilizing labeling algorithm of [11] that retains the initial algorithm as a module (Algorithm 4.2) allowing it to cope with reconfiguration.…”

Section: Labeling Scheme and Algorithmmentioning

confidence: 99%

“…If a reconfiguration is not taking place, then a member periodically sends to every other configuration member p j its own local maximal label and the last label that p j sent for the local maximal label. Note that messages from non-members are discarded before being sent, so they are not propagated (lines [6][7][8][9][10][11][12][13][14][15][16].…”

Section: Description Of Algorithm 41mentioning

confidence: 99%

“…The description of the inner workings of the labelReceptionAction() is given in great detail in [11]. As an overview, it first stores p j 's value in max i [j] and processes it along with the other label that was received which reflected p i 's maximal label that was received most recently by p j .…”

Section: Description Of Algorithm 41mentioning

confidence: 99%

“…In particular Algorithm 4.2 and line 16 comprise of the solution given in [11] to solve the fixed-set problem.…”

Section: Correctnessmentioning

confidence: 99%

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Self-stabilizing Reconfiguration

2017

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Current reconfiguration techniques are based on starting the system in a consistent configuration, in which all participating entities are in a predefined state. Starting from that state, the system must preserve consistency as long as a predefined churn rate of processors joins and leaves is not violated, and unbounded storage is available. Many working systems cannot control this churn rate and do not have access to unbounded storage. System designers that neglect the outcome of violating the above assumptions may doom the system to exhibit illegal behaviors. We present the first automatically recovering reconfiguration scheme that recovers from transient faults, such as temporal violations of the above assumptions. Our self-stabilizing solutions regain safety automatically by assuming temporal access to reliable failure detectors. Once safety is re-established, the failure detector reliability is no longer needed. Still, liveness is conditioned by the failure detector's unreliable signals. We show that our self-stabilizing reconfiguration techniques can serve as the basis for the implementation of several dynamic services over message passing systems. Examples include self-stabilizing reconfigurable virtual synchrony, which, in turn, can be used for implementing a self-stabilizing reconfigurable state-machine replication and self-stabilizing reconfigurable emulation of shared memory.

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Section: Applicationsmentioning

confidence: 99%

Section: Labeling Scheme and Algorithmmentioning

confidence: 99%

Section: Description Of Algorithm 41mentioning

confidence: 99%

Section: Description Of Algorithm 41mentioning

confidence: 99%

“…In particular Algorithm 4.2 and line 16 comprise of the solution given in [11] to solve the fixed-set problem.…”

Section: Correctnessmentioning

confidence: 99%

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Self-stabilizing Reconfiguration

2017

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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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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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Self-stabilizing Virtual Synchrony

Cited by 11 publications

References 16 publications

Self-stabilizing Reconfiguration

Self-stabilizing Reconfiguration

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

Self-stabilizing Virtual Synchrony

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