The text examines how computational intelligence can address the complex challenges and opportunities that arise in both wired and wireless networks. It discusses topics including fault tolerance and self-healing mechanisms, edge and fog computing, machine learning in wireless networks, quality of experience, and integration of emerging technologies.
This book:

• Introduces theoretical concepts, and demonstrates how computational intelligence techniques can be applied to solve real-world problems in network optimization, security, quality of experience, and resource allocation.                                             
• Discusses emerging technologies such as 5G and beyond, edge computing, and machine learning in the context of wired and wireless networks.                                    
• Presents the integration of machine learning concepts, including deep learning and reinforcement learning, in the context of wireless networks.                                             
• Highlights the use of computational intelligence techniques in enhancing network optimization by providing adaptive, self-learning, and efficient solutions.          
• Covers design, management, and optimization of networks using machine learning, deep learning, and reinforcement learning.           

It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields including electrical engineering, electronics and communication engineering, computer science and engineering, telecommunications, and information technology.