The evolution of networked systems, driven by innovations in software-defined networking (SDN), network function virtualization (NFV), open radio access networks (O-RAN), and cloud-native architectures, is redefining both the operational landscape and the threat surface of critical infrastructures. This book offers an in-depth, interdisciplinary examination of how resilience must be re-conceptualized and re-engineered to address the multifaceted challenges posed by these transformations. Structured across six chapters, this book begins by surveying the contemporary risk landscape, identifying emerging cyber, physical, and AI-driven threats, and analyzing their implications for scalable, heterogeneous network environments. It then establishes rigorous definitions and evaluation frameworks for resilience, going beyond robustness and fault-tolerance to address adaptive, anticipatory, and retrospective mechanisms across diverse application domains. The core of the book delves into advanced paradigms and practical strategies for resilience, including zero trust architectures, game-theoretic threat modeling, and self-healing design principles. A significant portion is devoted to the role of artificial intelligence, especially reinforcement learning and large language models (LLMs), in enabling dynamic threat response, autonomous network control, and multi-agent coordination under uncertainty.
Age of information (AoI) is a metric that quantifies the timeliness of information delivered in a system, which is an emerging requirement for a variety of services like autonomous driving, industrial internet of things, as well as the likes of mobile applications. This monograph presents an overview of AoI from the perspective of wireless networking. It gives a comprehensive introduction to the analytical techniques used in deriving this metric as well as networking strategies that improve the AoI. Extensions to other age-related metrics, applications, and future research directions are also discussed.
Cell-free (CF) integrated sensing and communication (ISAC) merges the CF architecture with ISAC functionalities. CF-ISAC leverages distributed access points, removes cell boundaries, and enhances coverage, spectral efficiency, and reliability. It also improves energy efficiency, enabling robust multi-user communication, distributed multi-static sensing, and seamless resource optimization. A comprehensive survey on CF-ISAC has been lacking. This monograph addresses that gap by covering the foundational principles, cooperative transmission, radar cross-section, target parameter estimation, ISAC integration levels, sensing metrics, and key applications. It also explores the advantages of multi-static sensing. Performance analysis, resource allocation, security, and user/ target-centric designs are discussed. Finally, synchronization, multi-target detection, interference management, and fronthaul limitations are discussed. Advanced antenna technologies, network-assisted systems, near-field CF-ISAC, cross-technology integration, and machine learning approaches are presented.
Robotic systems increasingly demand simultaneous high-precision sensing and low-latency communication-a duality that traditional disjoint architectures struggle to satisfy efficiently. Integrated Sensing and Communication (ISAC) addresses this challenge by unifying both functions within shared radio frequency and spectral resources, eliminating hardware redundancy and spectral inefficiency. This article surveys ISAC-enabled robotics, examining how joint waveform design, cross-layer protocols, and emerging technologies (mmWave, THz, in-band full-duplex transceivers) enable transformative applications. We focus on mission-critical scenarios where ISAC provides unique value: (1) factory robots achieving sub-centimeter positioning alongside millisecond-latency coordination for collision-free assembly, (2) surgical robots requiring simultaneous tissue imaging and instrument teleoperation with ultra-reliability, (3) autonomous vehicle platoons performing radar-based spacing control while exchanging cooperative maneuver plans, and (4) UAV swarms conducting distributed target tracking with bandwidth-efficient inter-agent communication. The article analyzes fundamental trade-offs in ISAC system design-sensing accuracy versus communication throughput, spectrum coexistence, RF front-end integration challenges, and security vulnerabilities arising from shared physical layers. We identify open research directions including AI-driven resource allocation, real-time co-optimization frameworks, and regulatory pathways for spectrum sharing. By consolidating sensing and communication primitives, ISAC emerges as an enabling infrastructure for autonomous robotic systems requiring tight perception-action coupling under stringent resource constraints.
Networks have changed significantly in recent decades, particularly with the emergence of SDN. This technology shapes and controls network traffic, focusing on policing techniques and more and more on Artificial Intelligence. This monograph analyzes how these technologies can enhance network performance, security, and scalability. Through detailed explanations of the theoretical foundations and practical applications, the monograph explores how SDN can be used to effectively manage network resources and traffic through the use of advanced models, real-time analysis, and integration with monitoring and anomaly detection tools. Each component is essential for optimizing network performance, particularly during dynamic loads and changing conditions. In addition to the theoretical framework, the monograph explains practical aspects, which will help both researchers and engineers in industry to understand better how to use SDN technologies to achieve effective traffic shaping and policing. Through an analysis of current challenges in the field of network management, a vision of the future of SDN is also given, with special emphasis on its application in various domains. The monograph is intended for anyone involved in the design, implementation, or management of SDN networks, whether academic researchers, engineers, or industry practitioners. We hope readers find useful information and tools to improve their knowledge and skills in modern network technologies.
