Distributed algorithms for message-passing systems

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Distributed computing is essential for applications that involve entities like processes, peers, or agents, each with limited knowledge of input parameters. Unlike parallel computing, which focuses on efficiency, and real-time computing, which emphasizes timely execution, distributed computing addresses the uncertainty stemming from multiple control flows, asynchronous communication, and dynamic behaviors. Although some distributed algorithms may appear simple, their behavior can be complex and challenging to analyze. This book aims to comprehensively present the fundamental concepts and algorithms of distributed computing, focusing on entities that communicate via asynchronous networks. It is organized into seventeen chapters across six parts: distributed graph algorithms, logical time and global states, mutual exclusion and resource allocation, high-level communication abstractions, distributed property detection, and distributed shared memory. Each chapter has clear objectives and is enriched with examples, summaries, exercises, and annotated bibliographies. This work serves as an introduction to distributed computing, targeting advanced undergraduates, graduate students in computer science and mathematics, and professionals involved in designing distributed applications. A basic understanding of algorithms and operating systems is recommended for readers.