In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers.



Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others.



The material is organized according to the system model-first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference.



The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms-to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.


Table of Contents

1 Introduction 
2 Modelling I; Synchronous Network Model 
3 Leader Election in a Synchronous Ring 
4 Algorithms in General Synchronous Networks 
5 Distributed Consensus with Link Failures 
6 Distributed Consensus with Process Failures 
7 More Consensus Problems 
8 Modelling II: Asynchronous System Model 
9 Modelling III: Asynchronous Shared Memory Model 
10 Mutual Exclusion 
11 Resource Allocation 
12 Consensus 
13 Atomic Objects 
14 Modelling IV: Asynchronous Network Model 
15 Basic Asynchronous Network Algorithms 
16 Synchronizers 
17 Shared Memory versus Networks 
18 Logical Time 
19 Global Snapshots and Stable Properties 
20 Network Resource Allocation 
21 Asynchronous Networks with Process Failures 
22 Data Link Protocols 
23 Partially Synchronous System Models 
24 Mutual Exclusion with Partial Synchrony 
25 Consensus with Partial Synchrony

Distributed algorithms

We survey results from distributed computing that show tasks to be impossible, either outright or within given resource bounds, in various models The parameters of the models considered include synchrony, fault-tolerance, different communication media, and randomization The resource bounds refer to time, space and message complexity These results are useful in understanding the inherent difficulty of individual problems and in studying the power of different models of distributed computing There is a strong emphasis in our presentation on explaining the wide variety of techniques that are used to obtain the results described

Hundreds of impossibility results for distributed computing

We study failure detectors in an asynchronous environment that admits message omission failures. In such environments, processes may fail by crashing, but may also {\em disconnect\/} from each other. We adapt Chandra and Toueg''s definitions of failure detection completeness and accuracy to the omissions failure model, and define a weak failure detector ><W(om) that allows any majority of the processes that become connected to reach a Consensus decision, despite any number of transient communication failures in their past. We provide a protocol that solves the Consensus problem in this model whenever a majority of the processes become connected, regardless of past omissions. Moreover, in our protocol it is not necessary to save and repeatedly send all past messages, which makes it more efficient than previous protocols in this model.

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Failure detectors in omission failure environments

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

Communication and Agreement Abstractions for Fault-Tolerant Asynchronous Distributed Systems

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.

Fault-Tolerant Message-Passing Distributed Systems: An Algorithmic Approach

Layered communication protocols frequently implement a FIFO message fiacility cm top of an unrehable non-FIFO serwce such as that provided hy a packet-swltchmg network. This paper investigates the possibdity of Implementing a reliable message layer on top of an underlying layer that can low packets and deliver them out of order, with the addltlonzd restriction that the implementatmn uses only a fixed fimte number of different packets. A new formalism is presented to spcclfy communication layers and their properties, the notion of their implementation by 1/0 automata. and the properties of such implementations. An 1/0 automaton that Implements a rellable layer over an unreliable layer is presented In this implementation, tbe number ot packets needed to deliver each succeeding message increases permanently as additional packet-loss and reordering faults occur. A proof is gwen that no protocol can avoid such performance degradatmn.

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Dai-Wei Wang

Papers

Reliable communication over unreliable channels