Chunxiao Jiang – författare

This book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book.

 Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today''s network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book.

With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development

 This book''s expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook.

This book targets major issues in terrestrial-satellite communication networks and presents the solutions. While the terrestrial networks can achieve high-speed data service at low cost, satellite based access is one way to complement terrestrial based networks to ensure ubiquitous, 100% geographic coverage. The coexistence and cooperation between terrestrial and satellite networks are of great potential in future communication networks, and satellite radio access networks has already been considered in the fifth-generation (5G) networks to be supported for phase 2. Therefore, it is important to study the architectures of terrestrial-satellite networks, as well as the possible techniques and challenges.

The expected audience for this book includes (but not limited to) graduate students, professors, researchers, scientists, practitioners, engineers, industry managers, and government researchers working in the field of satellite communications and networks.

With the growing popularity of “big data”, the potential value of personal data has attracted more and more attention. Applications built on personal data can create tremendous social and economic benefits. Meanwhile, they bring serious threats to individual privacy. The extensive collection, analysis and transaction of personal data make it difficult for an individual to keep the privacy safe. People now show more concerns about privacy than ever before. How to make a balance between the exploitation of personal information and the protection of individual privacy has become an urgent issue.

In this book, the authors use methodologies from economics, especially game theory, to investigate solutions to the balance issue. They investigate the strategies of stakeholders involved in the use of personal data, and try to find the equilibrium. 

The book proposes a user-role based methodology to investigate the privacy issues in data mining, identifying four different types of users, i.e. four user roles, involved in data mining applications. For each user role, the authors discuss its privacy concerns and the strategies that it can adopt to solve the privacy problems.

The authors discuss how the owners of data (e.g. an individual or a data miner) deal with the trade-off between privacy and utility in data mining. Specifically, they study users’ strategies in collaborative filtering based recommendation system and distributed classification system. They built game models to formulate the interactions among data owners, and propose learning algorithms to find the equilibria.

As an important future network architecture, virtual network architecture has received extensive attention. Virtual network embedding (VNE) is one of the core services of network virtualization (NV). It provides solutions for various network applications from the perspective of virtual network resource allocation. The Internet aims to provide global users with comprehensive coverage. The network function requests of hundreds of millions of end users have brought great pressure to the underlying network architecture. VNE algorithm can provide effective support for the reasonable and efficient allocation of network resources, so as to alleviate the pressure off the Internet.

At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users'' QoS requirements to avoid the waste of network resources.

Relying on unmanned autonomous flight control programs, unmanned aerial vehicles (UAVs) equipped with radio communication devices have been actively developed around the world. Given their low cost, flexible maneuvering and unmanned operation, UAVs have been widely used in both civilian operations and military missions, including environmental monitoring, emergency communications, express distribution, even military surveillance and attacks, for example. Given that a range of standards and protocols used in terrestrial wireless networks are not applicable to UAV networks, and that some practical constraints such as battery power and no-fly zone hinder the maneuverability capability of a single UAV, we need to explore advanced communication and networking theories and methods for the sake of supporting future ultra-reliable and low-latency applications. Typically, the full potential of UAV network’s functionalities can be tapped with the aid of the cooperation of multiple drones relying on their ad hoc networking, in-network communications and coordinated control. Furthermore, some swarm intelligence models and algorithms conceived for dynamic negotiation, path programming, formation flight and task assignment of multiple cooperative drones are also beneficial in terms of extending UAV’s functionalities and coverage, as well as of increasing their efficiency. We call the networking and cooperation of multiple drones as the terminology ‘flying ad hoc network (FANET)’, and there indeed are numerous new challenges to be overcome before the idespread of so-called heterogeneous FANETs. In this book, we examine a range of technical issues in FANETs, from physical-layer channel modeling to MAC-layer resource allocation, while also introducing readers to UAV aided mobile edge computing techniques.

To provide ubiquitous and various services, 6G networks tend to be more comprehensive and multidimensional by integrating current terrestrial networks with space-/air-based information networks and marine information networks; then, heterogeneous network resources, as well as different types of users and data, will be also integrated. Driven by the exponentially growing demands of multimedia data traffic and computation-heavy applications, 6G heterogenous networks are expected to achieve a high QoS with ultra-reliability and low latency. In response, resource allocation has been considered an important factor that can improve 6G performance directly by configuring heterogeneous communication, computing and caching resources effectively and efficiently. 

This book focuses on security science and technology, data and information security, and mobile and network security for space-air-ground integrated networks (SAGINs). SAGIN are expected to play an increasingly important role in providing real-time, flexible, and integrated communication and data transmission services in an efficient manner. Today, SAGINs have been widely developed for a range of applications in navigation, environmental monitoring, traffic management, counter-terrorism, etc. However, security becomes a major concern, since the satellites, spacecrafts, and aircrafts are susceptible to a variety of traditional/specific network-based attacks, including eavesdropping, session hijacking, and illegal access.

In this book, we review the theoretical foundations of SAGIN security. We also address a range of related security threats and provide cutting-edge solutions in the aspect of ground network security, airborne network security, space network security, and provide future trends in SAGIN security. The book goes from an introduction to the topic’s background, to a description of the basic theory, and then to cutting-edge technologies, making it suitable for readers at all levels including professional researchers and beginners. To gain the most from the book, readers should have taken prior courses in information theory, cryptography, network security, etc.