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A cognitive network is a network which can learn to improve its performance while operating under its unknown and dynamic environment. Cognitive engine as part of a cognitive network tries to adaptively find an appropriate configuration for the network. The cognitive networks such as cognitive radio networks, cognitive sensor networks, cognitive wireless mesh networks, cognitive mobile ad-hoc networks, and cognitive personal networks have received much attention in recent years. Up until now no peer-to-peer network management algorithm has been designated utilizing cognitive networking concepts. In this book, we adopt cognitive networking concepts and present a new framework for cognitive peer-to-peer networks and then propose an approach based on Dynamic Cellular Learning Automata for designing cognitive engines for solving network management problems in peer-to-peer networks.
About the author
Ali Mohammad Saghiri received the B. Sc. and M. Sc. degrees in computer engineering in Iran, in 2008 and 2010, respectively. He is currently the Ph.D. student of computer engineering in AmirKabir University of Technology, Tehran, Iran. His research interests include cognitive peer-to-peer networks, Artificial Intelligence, and soft computing.
