Distributed computation and optimization of large-scale networked systems are ubiquitous in all aspects of the interconnected world today. These applications range from signal processing and control systems to various areas of artificial intelligence. The emergence of big data applications has further stimulated researchers’ interest in distributed optimization. On the one hand, large datasets push centralized computing to its limits, and the need for distributed algorithms emerges naturally. On the other hand, transmitting data collected in a distributed manner to a center is too costly or may violate privacy. This book is dedicated to the optimization problem of information distribution over networked systems. Each agent in the network possesses private local information and solves the global optimization problem collaboratively through local computation and information exchange.