Modern network systems such as Internet of Things, Smart Grid, VoIP traffic, Peer-to-Peer protocol, and social networks, are inherently complex. They require powerful and realistic models and tools not only for analysis and simulation but also for prediction.This book covers important topics and approaches related to the modeling and simulation of complex communication networks from a complex adaptive systems perspective. The authors present different modeling paradigms and approaches as well as surveys and case studies.With contributions from an international panel of experts, this book is essential reading for networking, computing, and communications professionals, researchers and engineers in the field of next generation networks and complex information and communication systems, and academics and advanced students working in these fields.

Complex Systems are made up of numerous interacting sub-components. Non-linear interactions of these components or agents give rise to emergent behavior observable at the global scale. Agent-based modeling and simulation is a proven paradigm which has previously been used for effective computational modeling of complex systems in various domains. Because of its popular use across different scientific domains, research in agent-based modeling has primarily been vertical in nature. The goal of this manuscript is to provide a single hands-on guide to developing cognitive agent-based models for the exploration of emergence across various types of complex systems. We present practical ideas and examples for researchers and practitioners for the building of agent-based models using a horizontal approach - applications are demonstrated in a number of exciting domains as diverse as wireless sensors networks, peer-to-peer networks, complex social systems, research networks, epidemiological HIV​

Modern network systems such as Internet of Things, Smart Grid, VoIP traffic, Peer-to-Peer protocol, and social networks, are inherently complex. They require powerful and realistic models and tools not only for analysis and simulation but also for prediction.This book covers important topics and approaches related to the modeling and simulation of complex communication networks from a complex adaptive systems perspective. The authors present different modeling paradigms and approaches as well as surveys and case studies.With contributions from an international panel of experts, this book is essential reading for networking, computing, and communications professionals, researchers and engineers in the field of next generation networks and complex information and communication systems, and academics and advanced students working in these fields.

Complex Systems are made up of numerous interacting sub-components. Non-linear interactions of these components or agents give rise to emergent behavior observable at the global scale. Agent-based modeling and simulation is a proven paradigm which has previously been used for effective computational modeling of complex systems in various domains. Because of its popular use across different scientific domains, research in agent-based modeling has primarily been vertical in nature. The goal of this manuscript is to provide a single hands-on guide to developing cognitive agent-based models for the exploration of emergence across various types of complex systems. We present practical ideas and examples for researchers and practitioners for the building of agent-based models using a horizontal approach - applications are demonstrated in a number of exciting domains as diverse as wireless sensors networks, peer-to-peer networks, complex social systems, research networks, epidemiological HIV​