This book offers students and researchers a guide to distributed algorithms thatemphasizes examples and exercises rather than the intricacies of mathematical models. It avoidsmathematical argumentation, often a stumbling block for students, teaching algorithmic thoughtrather than proofs and logic. This approach allows the student to learn a large number of algorithmswithin a relatively short span of time. Algorithms are explained through brief, informaldescriptions, illuminating examples, and practical exercises. The examples and exercises allowreaders to understand algorithms intuitively and from different perspectives. Proof sketches,arguing the correctness of an algorithm or explaining the idea behind fundamental results, are alsoincluded. An appendix offers pseudocode descriptions of manyalgorithms.Distributed algorithms are performed by a collection of computers thatsend messages to each other or by multiple software threads that use the same shared memory. Thealgorithms presented in the book are for the most part "classics," selected because theyshed light on the algorithmic design of distributed systems or on key issues in distributedcomputing and concurrent programming. Distributed Algorithmscan be used in courses for upper-level undergraduates or graduate students in computer science, oras a reference for researchers in the field.