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

SPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from high-level descriptions of distributed algorithms to detailed code for controlling telephone exchanges. The paper gives an overview of the design and structure of the verifier, reviews its theoretical foundation, and gives an overview of significant practical applications.

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The model checker SPIN

The SPIN Model Checker is used for both teaching software verification techniques, and for validating large scale applications. The growing number of users has created a need for a more comprehensive user guide and a standard reference manual that describes the most recent version of the tool. This book fills that need. SPIN is used in over 40 countries. The offical SPIN web site, spinroot.com receives between 2500 and 3000 hits per day. It has been estimated that up to three-quarters of the $400 billion spent annually to hire programmers in the United States is ultimately spent on debugging

The SPIN Model Checker: Primer and Reference Manual

This survey covers rollback-recovery techniques that do not require special language constructs. In the first part of the survey we classify rollback-recovery protocols into checkpoint-based and log-based.Checkpoint-based protocols rely solely on checkpointing for system state restoration. Checkpointing can be coordinated, uncoordinated, or communication-induced. Log-based protocols combine checkpointing with logging of nondeterministic events, encoded in tuples called determinants. Depending on how determinants are logged, log-based protocols can be pessimistic, optimistic, or causal. Throughout the survey, we highlight the research issues that are at the core of rollback-recovery and present the solutions that currently address them. We also compare the performance of different rollback-recovery protocols with respect to a series of desirable properties and discuss the issues that arise in the practical implementations of these protocols.

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A survey of rollback-recovery protocols in message-passing systems

From the Publisher:
With an analytical and rigorous approach to problem solving and programming techniques,this book is oriented toward engineering. Structure and Interpretation of Computer Programs emphasizes the central role played by different approaches to dealing with time in computational models. Its unique approach makes it appropriate for an introduction to computer science courses,as well as programming languages and program design.

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Structure and Interpretation of Computer Programs

The problem of mutual exclusion - or of defining fundamental operations so that it is possible to resolve conflicts resulting from several concurrent processes sharing the resources of a computer system - has emerged over the last 20 years as a prime example of the difficulties associated with parallel or distributed programming. The implementation of a mutual exclusion mechanism, therefore, is a very real phenomenon that faces every designer of operating systems as well as applications programmers who use services provided by computer systems built around several processing units, or linked by a network. This book presents a remarkable survey of a vast field of concrete and highly complex research on algorithms for parallel or distributed control. Since parallelism makes it difficult to understand the behavior or to analyze the properties of algorithms that can solve these problems, all of the algorithms have been rewritten in a single language and restructured so that they are easy to understand and compare. The book systematically stresses the principles guiding their design, provides arguments to prove their validity and gives quantitative data allowing their assessment. Contents: Preface. The Nature of Control Problems in Parallel Processing. The Mutual Exclusion Problem in a Centralized Framework: Software Solutions. The Mutual Exclusion Problem in a Centralized Framework: Hardware Solutions. The Mutual Exclusion Problem in a Distributed Framework: Solutions Based on State Variables. The Mutual Exclusion Problem in a Distributed Framework: Solutions Based on Message Communication. Two Further Control Problems. M. Raynal is a professor, Department Informatique, IRISA-Universite deRennes 1, France. Algorithms for Mutual Exclusion is included in the Scientific Computation Series, edited by Dennis Gannon.

Algorithms for Mutual Exclusion

https://hal.inria.fr/inria-00075427/document

The causal ordering abstraction and a simple way to implement it

Causality is vital in distributed computations. Distributed systems can determine causality using logical clocks. Human beings use the concept of causality to plan, schedule, and execute an enterprise, or to determine a plan's feasibility. In daily life, we use global time to deduce causality from loosely synchronized clocks such as wrist watches and wall clocks. But in distributed computing systems, the rate of event occurrence is several magnitudes higher, and the event-execution time several magnitudes smaller. If the physical clocks in these systems are not synchronized precisely the causality relation between events cannot be captured accurately. However, distributed systems have no built-in physical time and can only approximate it. This article presents a general framework of a system of logical clocks in distributed systems and discusses three methods: scalar, vector and matrix, for implementing logical time in these systems.

Logical time: capturing causality in distributed systems

The advent of new architectures and computing platforms means that synchronization and concurrent computing are among the most important topics in computing science. Concurrent programs are made up of cooperating entities -- processors, processes, agents, peers, sensors -- and synchronization is the set of concepts, rules and mechanisms that allow them to coordinate their local computations in order to realize a common task. This book is devoted to the most difficult part of concurrent programming, namely synchronization concepts, techniques and principles when the cooperating entities are asynchronous, communicate through a shared memory, and may experience failures. Synchronization is no longer a set of tricks but, due to research results in recent decades, it relies today on sane scientific foundations as explained in this book. In this book the author explains synchronization and the implementation of concurrent objects, presenting in a uniform and comprehensive way the major theoretical and practical results of the past 30 years. Among the key features of the book are a new look at lock-based synchronization (mutual exclusion, semaphores, monitors, path expressions); an introduction to the atomicity consistency criterion and its properties and a specific chapter on transactional memory; an introduction to mutex-freedom and associated progress conditions such as obstruction-freedom and wait-freedom; a presentation of Lamport's hierarchy of safe, regular and atomic registers and associated wait-free constructions; a description of numerous wait-free constructions of concurrent objects (queues, stacks, weak counters, snapshot objects, renaming objects, etc.); a presentation of the computability power of concurrent objects including the notions of universal construction, consensus number and the associated Herlihy's hierarchy; and a survey of failure detector-based constructions of consensus objects. The book is suitable for advanced undergraduate students and graduate students in computer science or computer engineering, graduate students in mathematics interested in the foundations of process synchronization, and practitioners and engineers who need to produce correct concurrent software. The reader should have a basic knowledge of algorithms and operating systems.

Concurrent Programming: Algorithms, Principles, and Foundations

This paper addresses the Consensus problem in asynchronous distributed systems (made of n processes, at most f of them may crash) equipped with unreliable failure detectors. A generic Consensus protocol is presented: it is quorum-based and works with any failure detector belonging to the class S (provided that f ≤ n - 1) or to the class ⋄S (provided that f < n/2). This quorum-based generic approach for solving the Consensus problem is new (to our knowledge). Moreover, the proposed protocol is conceptually simple, allows early decision and uses messages shorter than previous solutions.

The generic dimension and the surprising design simplicity of the proposed protocol provide a better understanding of the basic algorithmic structures and principles that allow to solve the Consensus problem with the help of unreliable failure detectors.

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Michel Raynal

Papers

Algorithms for Mutual Exclusion

The causal ordering abstraction and a simple way to implement it

Logical time: capturing causality in distributed systems

Concurrent Programming: Algorithms, Principles, and Foundations

Solving Consensus Using Chandra-Toueg's Unreliable Failure Detectors: A General Quorum-Based Approach