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This thesis consists of three parts. The first part characterizes completely the shared-memory requirements for achieving agreement in an asynchronous system of fail-stop processes that die undetectably. There is no agreement protocol that uses only read and write operations, even if at most one process dies. This result implies the impossibility of Byzantine agreement in asynchronous message-passing systems. Furthermore, there is no agreement protocol that uses test-and-set operations if memory cells have only two values and two or more processes may die. In contrast, there is an agreement protocol with test-and-set operations if either memory cells have at least three values or at most one process dies. Part 2 considers the election problem on asynchronous complete networks when the processors are reliable but some of the channels may be intermittently faulty. To be consistent with the standard model of distributed algorithms in which channel delays can be arbitrary but finite, it is assumed that channel failures are undetectable. Given is an algorithm that correctly solves the problem when the channels fail before or during the execution of the algorithm. The third part presents the most efficient algorithm known of for election in synchronous square meshes. The algorithm uses 229/18n messages, runs in time units, and requires O(log(t)) bits per message. Also, we prove that any comparison algorithm on meshes requires at least 57/32n messages.
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.
There are several fault tolerant protocols for managing replicated files in the event of network partitioning due to site or communication link failures. Previously there has been no software simulation of the voting protocols apart from just stochastic modeling. In this paper, we simulate and analyze the throughput of message transfer during the communication. We use various network topologies to compare the parameters such as throughput, no of packets received and sent during voting process .We have analyzed the effects of various packet properties. The analysis provides evidence for the conjecture that the grouping scheme is the optimal algorithm in the context of the voting protocols. We also compare the proposed genetic approach for voting assignment with random algorithm proposed by Akhil Kumar. This comparison shows that genetic voting assignment gives better availability than random algorithm.
This volume contains papers presented at the First International Workshop on Distributed Algorithms. The papers present solutions to a wide spectrum of problems (leader election, resource allocation, routing, etc.) and focus on a variety of issues that influence communications complexity.
Dotyczy: gossiping, consensus, distributed algorithms, fault tolerance, adaptive algorithms, processor failures, quantum algorithms.
This book investigates theoretical aspects of system models for agreement problems in fault-tolerant distributed computing. A distributed system is a collection of processes that communicate with each other by sending messages over a network. Achieving agreement among these processes despite failures is a difficult but important problem. Care must be taken when choosing a system model as a too restrictive model will be applicable to very few systems, whereas too relaxed assumptions might severely reduce the set of problems that can be solved. Part I of this book provides an introduction to the context of this work, discusses related literature and describes the basic system assumptions. Part II introduces the Asynchronous Bounded-Cycle model which is entirely time-free but nevertheless sufficient to solve fault-tolerant consensus despite Byzantine faults. Part III presents an in-depth treatment of algorithms and models for solving the k-set agreement problem which requires processes to agree on at most k distinct values.