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Understanding distributed computing is not an easy task. This is due to the many facets of uncertainty one has to cope with and master in order to produce correct distributed software. Considering the uncertainty created by asynchrony and process crash failures in the context of message-passing systems, the book focuses on the main abstractions that one has to understand and master in order to be able to produce software with guaranteed properties. These fundamental abstractions are communication abstractions that allow the processes to communicate consistently (namely the register abstraction and the reliable broadcast abstraction), and the consensus agreement abstractions that allows them to cooperate despite failures. As they give a precise meaning to the words "communicate" and "agree" despite asynchrony and failures, these abstractions allow distributed programs to be designed with properties that can be stated and proved. Impossibility results are associated with these abstractions. Hence, in order to circumvent these impossibilities, the book relies on the failure detector approach, and, consequently, that approach to fault-tolerance is central to the book. Table of Contents: List of Figures / The Atomic Register Abstraction / Implementing an Atomic Register in a Crash-Prone Asynchronous System / The Uniform Reliable Broadcast Abstraction / Uniform Reliable Broadcast Abstraction Despite Unreliable Channels / The Consensus Abstraction / Consensus Algorithms for Asynchronous Systems Enriched with Various Failure Detectors / Constructing Failure Detectors
This book presents the most important fault-tolerant distributed programming abstractions and their associated distributed algorithms, in particular in terms of reliable communication and agreement, which lie at the heart of nearly all distributed applications. These programming abstractions, distributed objects or services, allow software designers and programmers to cope with asynchrony and the most important types of failures such as process crashes, message losses, and malicious behaviors of computing entities, widely known under the term "Byzantine fault-tolerance". The author introduces these notions in an incremental manner, starting from a clear specification, followed by algorithms which are first described intuitively and then proved correct. The book also presents impossibility results in classic distributed computing models, along with strategies, mainly failure detectors and randomization, that allow us to enrich these models. In this sense, the book constitutes an introduction to the science of distributed computing, with applications in all domains of distributed systems, such as cloud computing and blockchains. Each chapter comes with exercises and bibliographic notes to help the reader approach, understand, and master the fascinating field of fault-tolerant distributed computing.
The present book focuses on the way to cope with the uncertainty created by process failures (crash, omission failures and Byzantine behavior) in synchronous message-passing systems (i.e., systems whose progress is governed by the passage of time). To that end, the book considers fundamental problems that distributed synchronous processes have to solve. These fundamental problems concern agreement among processes (if processes are unable to agree in one way or another in presence of failures, no non-trivial problem can be solved). They are consensus, interactive consistency, k-set agreement and non-blocking atomic commit. Being able to solve these basic problems efficiently with provable guarantees allows applications designers to give a precise meaning to the words "cooperate" and "agree" despite failures, and write distributed synchronous programs with properties that can be stated and proved. Hence, the aim of the book is to present a comprehensive view of agreement problems, algorithms that solve them and associated computability bounds in synchronous message-passing distributed systems. Table of Contents: List of Figures / Synchronous Model, Failure Models, and Agreement Problems / Consensus and Interactive Consistency in the Crash Failure Model / Expedite Decision in the Crash Failure Model / Simultaneous Consensus Despite Crash Failures / From Consensus to k-Set Agreement / Non-Blocking Atomic Commit in Presence of Crash Failures / k-Set Agreement Despite Omission Failures / Consensus Despite Byzantine Failures / Byzantine Consensus in Enriched Models
Abstract: "A termination detector is a distributed algorithm that, when superimposed on a distributed system of n processes, is able to determine whether the computation of the underlying system has terminated. Fault tolerance is one of the most desirable properties of distributed systems. While some problems are notoriously known to be unsolvable in the presence of faulty processes, many distributed algorithms are able to tolerate failures of processes. When a termination detector is applied to a fault-tolerant underlying system, it is desirable that the detector itself be fault-tolerant. In most existing distributed systems, processes certainly may fail, but only occasionally or even rarely. Thus, a desirable fault-tolerant algorithm is one that can tolerate any number of faults, that runs as efficiently as the best available non-fault-tolerant algorithm if no process fails during the computation, and that incurs only a reasonable amount of extra cost for each process failure that actually occurs. In this paper, we present a fault-tolerant termination detection algorithm with these nice properties. The algorithm is much more efficient than existing (fault-tolerant) ones."
Dotyczy: gossiping, consensus, distributed algorithms, fault tolerance, adaptive algorithms, processor failures, quantum algorithms.
Abstract: "A fault tolerant termination detection scheme is proposed. The scheme is distributed and symmetry. It can be applied to any kind of connection topology. It uses the FIFO property of a single transmission line to cope with system wide non-FIFO message transmission. Some of the information concerning termination detection are backed up for fault tolerant purpose [sic]. The backing up does not require the synchronisation of the processing nodes, and it does not interfere with the normal computation. Hence, The [sic] overhead to achieve fault tolerance has been minimised. The scheme is derived using invariant technique [sic]."
So far, the distributed computing community has either assumed that all the processes of a distributed system have distinct identifiers or, more rarely, that the processes are anonymous and have no identifiers. These are two extremes of the same general model: namely, n processes use l different identifiers, where 1 l n. We call this model homonymous model. To determine the power of homonymous model as well as the importance of identi ers in distributed computing, this thesis studies algorithms for solving the consensus problem, one of the most famous distributed computing problem."
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