Distributed Algorithms for Message-Passing Systems

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Distributed computing is essential for many applications, addressing problems where entities—like processes, peers, or nodes—possess only partial knowledge of input parameters. Unlike parallel computing, which focuses on efficiency, and real-time computing, which emphasizes timely execution, distributed computing aims to manage uncertainty stemming from multiple control flows, asynchronous communication, and dynamic behaviors. While some distributed algorithms are concise, their behavior can be complex, making their properties challenging to understand and prove. This book provides a comprehensive overview of fundamental concepts and algorithms in distributed computing, particularly in contexts where entities communicate asynchronously. It comprises seventeen chapters divided into six parts, covering topics such as distributed graph algorithms, logical time and global states, mutual exclusion, resource allocation, high-level communication abstractions, property detection, and distributed shared memory. Each chapter has clear objectives, supported by examples, summaries, exercises, and annotated bibliographies. This work serves as an introduction to distributed computing, targeting advanced undergraduates, graduate students in computer science or mathematics, and practitioners involved in distributed application design. A basic understanding of algorithms and operating systems is recommended for readers.