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This book constitutes the refereed proceedings of the 20th International Conference on Distributed Computing and Intelligent Technology, ICDCIT 2024, which was held in Bhubaneswar, India, during January 17–20, 2024. The 24 full papers presented in this volume were carefully reviewed and selected from 116 submissions. The papers are organized in the following topical sections: Distributed Computing (DC) and Intelligent Technology (IT). The DC track solicits original research papers contributing to the foundations and applications of distributed computing, whereas the IT track solicits original research papers contributing to the foundations and applications of Intelligent Technology.

This book constitutes the proceedings of 24th International Symposium, SSS 2022, which took place in Clermont-Ferrand, France, in November 2022.The 17 regular papers together with 4 invited papers and 7 brief announcements, included in this volume were carefully reviewed and selected from 58 submissions. The SSS 2022 focus on systems built such that they are able to provide on their own guarantees on their structure, performance, and/or security in the face of an adverse environment. The Symposium presents three tracks reflecting major trends related to the conference: (i) Self-stabilizing Systems: Theory and Practice, (ii) Concurrent and Distributed Computing: Foundations, Faulttolerance, and Security, and (iii) Dynamic, Mobile, and Nature-Inspired Computing.

This book constitutes the refereed proceedings of the 22nd International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2020, held in Austin, TX, USA, in November 2020.The 16 full papers, 7 short and 2 invited papers presented were carefully reviewed and selected from 44 submissions. The papers deal with the design and development of distributed systems with a focus on systems that are able to provide guarantees on their structure, performance, and/or security in the face of an adverse operational environment.

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 an 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.

This book constitutes the refereed proceedings of the 13th International Conference on Distributed Computing and Networking, ICDCN 2012, held in Hong Kong, China, during January 3-6, 2012.The 36 revised full papers and 1 short paper presented together with 4 poster papers were carefully reviewed and selected from 100 submissions. The papers address all current issues in the field of distributed computing and networking. Being a leading forum for researchers and practitioners to exchange ideas and share best practices, ICDCN also hosts as a forum for PhD students to discuss their research ideas and get quality feedback from the well-renowned experts in the field of distributed computing and computer networking.