This book studies algorithmic issues associated with cooperative execution of multiple independent tasks by distributed computing agents including partitionable networks. It provides the most significant algorithmic solution developed and available today for do-all computing for distributed systems (including partitionable networks), and is the first monograph that deals with do-all computing for distributed systems. Recent results have shed light on the understanding of how adversity affects efficiency, by presenting failure-sensitive upper and lower bounds for Do-All in several models for computation. The ability to cooperatively perform a collection of tasks is key to solving a broad array of computation problems ranging from distributed search to distributed simulation and multi-agent collaboration which is introduced within this book.
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