Andreas Pitsillides – författare

The aim of this book is to delineate the challenges faced by new generation mobile networks, such as 5G and forthcoming 6G, and introduce the concept of addressing these challenges through the development of a novel Distributed AI (DAI) framework. The book proposes a distributed AI approach to handle these complexities effectively.Distributed Artificial Intelligence for 5G/6G Communications: Frameworks with Machine Learning aims to provide a comprehensive understanding of the proposed DAI framework, its architecture, implementation, and application in the context of D2D communication in 5G and beyond networks. It showcases how the framework can enhance decision-making, control, and communication performance while considering both static and dynamic network environments. The book delves into the advantages of D2D communication, highlighting how it transcends licensed frequency bands and bypasses the cellular network, leading to improved network metrics such as spectral efficiency, energy efficiency, data rates, and interference management. It concludes by emphasizing that the DAI framework can offer enhanced network control, reduced signaling overhead, and efficient decision-making while capitalizing on existing implementations to tackle various challenges across the 5G and 6G landscape.This book is intended for professionals that specialize in designing, implementing, and maintaining communication networks such as telecommunications/ communication engineers, wireless engineers. The book's emphasis on incorporating AI and ML techniques in the proposed framework also makes it of interest to computer and software engineers working in artificial intelligence and machine learning engineers.

The aim of this book is to delineate the challenges faced by new generation mobile networks, such as 5G and forthcoming 6G, and introduce the concept of addressing these challenges through the development of a novel Distributed AI (DAI) framework. The book proposes a distributed AI approach to handle these complexities effectively.Distributed Artificial Intelligence for 5G/6G Communications: Frameworks with Machine Learning aims to provide a comprehensive understanding of the proposed DAI framework, its architecture, implementation, and application in the context of D2D communication in 5G and beyond networks. It showcases how the framework can enhance decision-making, control, and communication performance while considering both static and dynamic network environments. The book delves into the advantages of D2D communication, highlighting how it transcends licensed frequency bands and bypasses the cellular network, leading to improved network metrics such as spectral efficiency, energy efficiency, data rates, and interference management. It concludes by emphasizing that the DAI framework can offer enhanced network control, reduced signaling overhead, and efficient decision-making while capitalizing on existing implementations to tackle various challenges across the 5G and 6G landscape.This book is intended for professionals that specialize in designing, implementing, and maintaining communication networks such as telecommunications/ communication engineers, wireless engineers. The book's emphasis on incorporating AI and ML techniques in the proposed framework also makes it of interest to computer and software engineers working in artificial intelligence and machine learning engineers.

A mathematical tool for scientists and researchers who work with computer and communication networks, Game Theory in Communication Networks: Cooperative Resolution of Interactive Networking Scenarios addresses the question of how to promote cooperative behavior in interactive situations between heterogeneous entities in communication networking scenarios. It explores network design and management from a theoretical perspective, using game theory and graph theory to analyze strategic situations and demonstrate profitable behaviors of the cooperative entities.The book promotes the use of Game Theory to address important resource management and security issues found in next generation communications networks, particularly heterogeneous networks, for cases where cooperative interactive networking scenarios can be formulated. It provides solutions for representative mechanisms that need improvement by presenting a theoretical step-by-step approach. The text begins with a presentation of theory that can be used to promote cooperation for the entities in a particular interactive situation. Next, it examines two-player interaction as well as interactions between multiple players. The final chapter presents and examines a performance evaluation framework based on MATLAB®.Each chapter begins by introducing basic theory for dealing with a particular interactive situation and illustrating how particular aspects of game theory can be used to formulate and solve interactive situations that appear in communication networks regularly. The second part of each chapter presents example scenarios that demonstrate the applicability and power of the theory—illustrating a number of cooperative interactions and discussing how they could be addressed within the theoretical framework presented in the first part of the chapter. The book also includes simulation code that can be downloaded so you can use some or all of the proposed models to improve your own network designs. Specific topics covered include network selection, user-network interaction, network synthesis, and context-aware security provisioning.

Comprehension of complex systems comes from an understanding of not only the behavior of constituent elements but how they act together to form the behavior of the whole. However, given the multidisciplinary nature of complex systems, the scattering of information across different areas creates a chaotic situation for those trying to understand possible solutions and applications.Modeling and Control of Complex Systems brings together a number of research experts to present some of their latest approaches and future research directions in a language accessible to system theorists. Contributors discuss complex systems such as networks for modeling and control of civil structures, vehicles, robots, biomedical systems, fluid flow systems, and home automation systems. Each chapter provides theoretical and methodological descriptions of a specific application in the control of complex systems, including congestion control in computer networks, autonomous multi-robot docking systems, modeling and control in cancer genomics, and backstepping controllers for stabilization of turbulent flow PDEs.With this unique reference, you will discover how complexity is dealt with in different disciplines and learn about the latest methodologies, which are applicable to your own specialty. The balanced mix of theory and simulation presented by Modeling and Control of Complex Systems supplies a strong vehicle for enlarging your knowledge base a fueling future advances and incredible breakthroughs.