Scaling Laws of Network Value

Cheng Wang is a Professor at the School of Computer Science and Technology, Tongji University. His research focuses on large-scale communication networks, distributed systems, and intelligent computing—areas that closely relate to the study of system scalability explored in this book. Professor Wang has authored more than 150 peer-reviewed publications and holds 34 invention patents. He has led several national-level research initiatives, including the National Key Research and Development Program of the Ministry of Science and Technology and the Industrial Internet Innovation and Development Program of the Ministry of Industry and Information Technology. His academic contributions have been recognized with major distinctions such as the National Science and Technology Progress Award and the Outstanding Ph.D. Dissertation Award from the China Computer Federation (CCF). Professor Wang has published several books with Springer, including Human Factor Security and Safety (2025), Computational Structural Behavior (2026), and Integrated Security and Safety of Intelligent Computing (2026).  Yuhang Lin is a PhD candidate in the School of Computer Science and Technology at Tongji University. His research interests include information theory, behavioral computing and network representation learning.

• Chapter 1: Introduction and Overview.- Chapter 2: Scaling Laws of Self-Organized Communication Networks: Throughput Capacity.- Chapter 3: Scaling Laws of Self-Organized Communication Networks: Transport Complexity.- Chapter 4: Scaling Laws of Deep-Learning Neural Networks: Taxonomy and Survey.- Chapter 5: Scaling Laws of Deep-Learning Neural Networks: Expressive Power.- Chapter 6: Scaling Laws of Deep-Learning Neural Networks: Information Loss.