Karine Altisen, Stephane Devismes, Swan Dubois, Franck Petit Introduction to Distributed Self-Stabilizing Algorithms 9781681735368

Варианты приобретения

Цена: 72070.00T
Кол-во:
о цене
Наличие: Отсутствует.
Возможна поставка под заказ. Дата поступления на склад уточняется после оформления заказа

Добавить в корзину

в Мои желания

Автор: Karine Altisen, Stephane Devismes, Swan Dubois, Franck Petit
Название: Introduction to Distributed Self-Stabilizing Algorithms
ISBN: 9781681735368
Издательство: Mare Nostrum (Eurospan)
Классификация:

Компьютерное программирование / разработка по

Алгоритмы и структуры данных

Компьютерные сети и коммуникации

Параллельная обработка данных

ISBN-10: 1681735369
Обложка/Формат: Paperback
Страницы: 165
Вес: 0.29 кг.
Дата издания: 30.04.2019
Серия: Synthesis lectures on distributed computing theory
Язык: English
Размер: 235 x 191 x 9
Читательская аудитория: Professional and scholarly
Ключевые слова: Computer networking & communications,Computer programming / software development,Parallel processing, COMPUTERS / Networking / General,COMPUTERS / Systems Architecture / Distributed Systems & Computing,COMPUTERS / Programming / Algorithms
Рейтинг:
Поставляется из: Англии
Описание: This book aims at being a comprehensive and pedagogical introduction to the concept of self-stabilization , introduced by Edsger Wybe Dijkstra in 1973. Self-stabilization characterizes the ability of a distributed algorithm to converge within finite time to a configuration from which its behavior is correct (i.e., satisfies a given specification), regardless the arbitrary initial configuration of the system. This arbitrary initial configuration may be the result of the occurrence of a finite number of transient faults. Hence, self-stabilization is actually considered as a versatile non-masking fault tolerance approach, since it recovers from the effect of any finite number of such faults in a unified manner. Another major interest of such an automatic recovery method comes from the difficulty of resetting malfunctioning devices in a large-scale (and so, geographically spread) distributed system (the Internet, Pair-to-Pair networks, and Delay Tolerant Networks are examples of such distributed systems). Furthermore, self-stabilization is usually recognized as a lightweight property to achieve fault tolerance as compared to other classical fault tolerance approaches. Indeed, the overhead, both in terms of time and space, of state-of-the-art self-stabilizing algorithms is commonly small. This makes self-stabilization very attractive for distributed systems equipped of processes with low computational and memory capabilities, such as wireless sensor networks. After more than 40 years of existence, self-stabilization is now sufficiently established as an important field of research in theoretical distributed computing to justify its teaching in advanced research-oriented graduate courses. This book is an initiation course, which consists of the formal definition of self-stabilization and its related concepts, followed by a deep review and study of classical (simple) algorithms, commonly used proof schemes and design patterns, as well as premium results issued from the self-stabilizing community. As often happens in the self-stabilizing area, in this book we focus on the proof of correctness and the analytical complexity of the studied distributed self-stabilizing algorithms. Finally, we underline that most of the algorithms studied in this book are actually dedicated to the high-level atomic-state model , which is the most commonly used computational model in the self-stabilizing area. However, in the last chapter, we present general techniques to achieve self-stabilization in the low-level message passing model, as well as example algorithms.

Introduction to Distributed Self-Stabilizing Algorithms, Karine Altisen, Stephane Devismes, Swan Dubois, Franck Petit