This brief examines current research on improving Vehicular Networks (VANETs), examining spectrum scarcity due to the dramatic growth of mobile data traffic and the limited bandwidth of dedicated vehicular communication bands and the use of opportunistic spectrum bands to mitigate congestion. It reviews existing literature on the use of opportunistic spectrum bands for VANETs, including licensed and unlicensed spectrum bands and a variety of related technologies, such as cognitive radio, WiFi and device-to-device communications. Focused on analyzing spectrum characteristics, designing efficient spectrum exploitation schemes, and evaluating the date delivery performance when utilizing different opportunistic spectrum bands, the results presented in this brief provide valuable insights on improving the design and deployment of future VANETs.
This book provides a comprehensive overview of the emerging technologies for next-generation 5G mobile communications, with insights into the long-term future of 5G. Written by international leading experts on the subject, this contributed volume covers a wide range of technologies, research results, and networking methods. Key enabling technologies for 5G systems include, but are not limited to, millimeter-wave communications, massive MIMO technology and non-orthogonal multiple access.
5G will herald an even greater rise in the prominence of mobile access based upon both human-centric and machine-centric networks. Compared with existing 4G communications systems, unprecedented numbers of smart and heterogeneous wireless devices will be accessing future 5G mobile systems. As a result, a new paradigm shift is required to deal with challenges on explosively growing requirements in mobile data traffic volume (1000x), number of connected devices (10-100x), typical end-user data rate (10-100x), and device/network lifetime (10x). Achieving these ambitious goals calls for revolutionary candidate technologies in future 5G mobile systems.
Designed for researchers and professionals involved with networks and communication systems, 5G Mobile Communications is a straightforward, easy-to-read analysis of the possibilities of 5G systems.
This SpringerBrief covers the security and privacy challenges in fog computing, and proposes a new secure and privacy-preserving mechanisms to resolve these challenges for securing fog-assisted IoT applications. Chapter 1 introduces the architecture of fog-assisted IoT applications and the security and privacy challenges in fog computing. Chapter 2 reviews several promising privacy-enhancing techniques and illustrates examples on how to leverage these techniques to enhance the privacy of users in fog computing. Specifically, the authors divide the existing privacy-enhancing techniques into three categories: identity-hidden techniques, location privacy protection and data privacy enhancing techniques. The research is of great importance since security and privacy problems faced by fog computing impede the healthy development of its enabled IoT applications. With the advanced privacy-enhancing techniques, the authors propose three secure andprivacy-preserving protocols for fog computing applications, including smart parking navigation, mobile crowdsensing and smart grid. Chapter 3 introduces identity privacy leakage in smart parking navigation systems, and proposes a privacy-preserving smart parking navigation system to prevent identity privacy exposure and support efficient parking guidance retrieval through road-side units (fogs) with high retrieving probability and security guarantees. Chapter 4 presents the location privacy leakage, during task allocation in mobile crowdsensing, and propose a strong privacy-preserving task allocation scheme that enables location-based task allocation and reputation-based report selection without exposing knowledge about the location and reputation for participators in mobile crowdsensing. Chapter 5 introduces the data privacy leakage in smart grid, and proposes an efficient and privacy-preserving smart metering protocol to allow collectors (fogs) to achieve real-time measurement collection with privacy-enhanced data aggregation. Finally, conclusions and future research directions are given in Chapter 6. This brief validates the significant feature extension and efficiency improvement of IoT devices without sacrificing the security and privacy of users against dishonest fog nodes. It also provides valuable insights on the security and privacy protection for fog-enabled IoT applications. Researchers and professionals who carry out research on security and privacy in wireless communication will want to purchase this SpringerBrief. Also, advanced level students, whose main research area is mobile network security will also be interested in this SpringerBrief.
This book examines recent research on designing online charging and discharging strategies for mobile electric vehicles (EVs) in smart grid. First, the architecture and applications are provided. Then, the authors review the existing works on charging and discharging strategy design for EVs. Critical challenges and research problems are identified. Promising solutions are proposed to accommodate the issues of high EV mobility, vehicle range anxiety, and power systems overload. The authors investigate innovating charging and discharging potentials for mobile EVS based on real-time information collections (via VANETS and/or cellular networks) and offer the power system adjustable load management methods. Several innovative charging/discharging strategy designs to address the challenging issues in smart grid, i.e., overload avoidance and range anxiety for individual EVs, are presented. This book presents an alternative and promising way to release the pressure of the power grid caused by peak-time EV charging demand. Mobile Electric Vehicles: Online Charging and Discharging provides valuable insights on charging/ discharging strategy design for mobile EVs and the power system management in a smart grid. The authors' findings indicate that the proposed strategies considerably outperform the traditional EV charging strategies without real-time collections on the metrics of the overall energy utilization, the average EV travel cost and the number of successfully charged EVs. Research and graduate students who are working on smart grid and vehicular communication will find this book a valuable resource. Customs and systems operators will also find this book useful.
This Springer Brief discusses efficient security protocols and schemes for multi-hop wireless networks. It presents an overview of security requirements for these networks, explores challenges in securing networks and presents system models. The authors introduce mechanisms to reduce the overhead and identify malicious nodes that drop packets intentionally. Also included is a new, efficient cooperation incentive scheme to stimulate the selfish nodes to relay information packets and enforce fairness. Many examples are provided, along with predictions for future directions of the field. Security for Multi-hop Wireless Networks demonstrates recent research that enhances the efficiency and safety of these key networks. Concise and practical, it is a useful tool for researchers and professionals working in network security. It is also a valuable resource for advanced-level students interested in wireless communications and networking.
This Springer Brief focuses on cognitive resource management in heterogeneous cellular networks (Het Net) with small cell deployment for the LTE-Advanced system. It introduces the Het Net features, presents practical approaches using cognitive radio technology in accommodating small cell data relay and optimizing resource allocation and examines the effectiveness of resource management among small cells given limited coordination bandwidth and wireless channel uncertainty. The authors introduce different network characteristics of small cell, investigate the mesh of small cell access points in parallel with macrocells in network control and resource management and address resource management in the backhaul with coordination constraints and wireless channel uncertainty. The final section of this brief summarizes and provides future research directions for this topic, including a proposed framework that has been evaluated through realistic simulations. Cognitive Resource Management for Heterogeneous Cellular Networks is designed for researchers and professionals working in wireless communications and networks. Advanced-level students studying electrical and computer engineering should also find the content helpful.
This Springer Brief covers emerging maritime wideband communication networks and how they facilitate applications such as maritime distress, urgency, safety and general communications. It provides valuable insight on the data transmission scheduling and protocol design for the maritime wideband network. This brief begins with an introduction to maritime wideband communication networks including the architecture, framework, operations and a comprehensive survey on current developments. The second part of the brief presents the resource allocation and scheduling for video packet transmission with a goal of maximizing the weights of uploaded video packets. Finally, an energy and content aware scheduling scheme is proposed for the most efficient vessel packet throughput. Based on the real ship route traces obtained from the navigation software BLM-Ship, simulation results demonstrate the viability of the proposed schemes. Conclusions and further research directions are discussed. Maritime Wideband Communication Networks: Video Transmission Scheduling is a valuable tool for researchers and professionals working in wireless communications and networks. Advanced-level students studying computer science and electrical engineering will also find the content valuable.
This SpringerBrief presents key enabling technologies and state-of-the-art research on delivering efficient content distribution services to fast moving vehicles. It describes recent research developments and proposals towards the efficient, resilient and scalable content distribution to vehicles through both infrastructure-based and infrastructure-less vehicular networks. The authors focus on the rich multimedia services provided by vehicular environment content distribution including vehicular communications and media playback, giving passengers many infotainment applications. Common problems of vehicular network research are addressed, including network design and optimization, standardization, and the adaptive playout from a user's perspective.
This SpringerBrief focuses on the network capacity analysis of VANETs, a key topic as fundamental guidance on design and deployment of VANETs is very limited. Moreover, unique characteristics of VANETs impose distinguished challenges on such an investigation. This SpringerBrief first introduces capacity scaling laws for wireless networks and briefly reviews the prior arts in deriving the capacity of VANETs. It then studies the unicast capacity considering the socialized mobility model of VANETs. With vehicles communicating based on a two-hop relaying scheme, the unicast capacity bound is derived and can be applied to predict the throughput of real-world scenarios of VANETs.
The downlink capacity of VANETs is also investigated in which access infrastructure is deployed to provide pervasive Internet access to vehicles. Different alternatives of wireless access infrastructure are considered. A lower bound of downlink capacity is derived for each type of access infrastructure. The last section of this book presents a case study based on a perfect city grid to examine the capacity-cost trade-offs of different deployments since the deployment costs of different access infrastructure are highly variable.
This book provides a comprehensive investigation on new technologies for future vehicular networks. The authors propose different schemes to efficiently manage the multi-dimensional resources for supporting diversified applications. The authors answer the questions of why connected and automated vehicle technology should be considered; how the multi-access edge computing (MEC) and unmanned aerial vehicle (UAV) technologies can be helpful to vehicular networks; how to efficiently manage the multi-dimensional resources to support different vehicular applications with guaranteed quality-of-service (QoS) requirements; and how to adopt optimization and AI technologies to achieve resource management in vehicular networks. The book is pertinent to researchers, professionals, academics and students in vehicular technologies.
This book presents the security and privacy challenges of the smart home following the logic of "terminal device - voice interface - application platform". For each component, the authors provide answers to the three questions: 1) In the terminal device layer, how to conduct cross-layer privacy breach analysis and provide effective countermeasures; 2) In the voice interface layer, how to design effective and lightweight schemes to defend against voice spoofing; 3) In the application layer, how to design an effective anomaly detection system without breaching the application platform. The authors conduct a thorough analysis of the security threats and challenges in each component of the smart home, review the existing state-of-the-art solutions proposed by other researchers, and elaborate on proposed countermeasures. This book aims to provide both security threats analysis and state-of-the-art countermeasures for the smart home network.
This book introduces a new type of data poisoning attack, dubbed, backdoor attack. In backdoor attacks, an attacker can train the model with poisoned data to obtain a model that performs well on a normal input but behaves wrongly with crafted triggers. Backdoor attacks can occur in many scenarios where the training process is not entirely controlled, such as using third-party datasets, third-party platforms for training, or directly calling models provided by third parties. Due to the enormous threat that backdoor attacks pose to model supply chain security, they have received widespread attention from academia and industry. This book focuses on exploiting backdoor attacks in the three types of DNN applications, which are image classification, natural language processing, and federated learning.
Based on the observation that DNN models are vulnerable to small perturbations, this book demonstrates that steganography and regularization can be adopted to enhance the invisibility of backdoor triggers. Based on image similarity measurement, this book presents two metrics to quantitatively measure the invisibility of backdoor triggers. The invisible trigger design scheme introduced in this book achieves a balance between the invisibility and the effectiveness of backdoor attacks. In the natural language processing domain, it is difficult to design and insert a general backdoor in a manner imperceptible to humans. Any corruption to the textual data (e.g., misspelled words or randomly inserted trigger words/sentences) must retain context-awareness and readability to human inspectors. This book introduces two novel hidden backdoor attacks, targeting three major natural language processing tasks, including toxic comment detection, neural machine translation, and question answering, depending on whether the targeted NLP platform accepts raw Unicode characters.
The emerged distributed training framework, i.e., federated learning, has advantages in preserving users' privacy. It has been widely used in electronic medical applications, however, it also faced threats derived from backdoor attacks. This book presents a novel backdoor detection framework in FL-based e-Health systems. We hope this book can provide insightful lights on understanding the backdoor attacks in different types of learning-based algorithms, including computer vision, natural language processing, and federated learning. The systematic principle in this book also offers valuable guidance on the defense of backdoor attacks against future learning-based algorithms.
This book investigates novel accurate and efficient privacy-preserving techniques and their applications in e-Healthcare services. The authors first provide an overview and a general architecture of e-Healthcare and delve into discussions on various applications within the e-Healthcare domain. Simultaneously, they analyze the privacy challenges in e-Healthcare services. Then, in Chapter 2, the authors give a comprehensive review of privacy-preserving and machine learning techniques applied in their proposed solutions. Specifically, Chapter 3 presents an efficient and privacy-preserving similar patient query scheme over high-dimensional and non-aligned genomic data; Chapter 4 and Chapter 5 respectively propose an accurate and privacy-preserving similar image retrieval scheme and medical pre-diagnosis scheme over dimension-related medical images and single-label medical records; Chapter 6 presents an efficient and privacy-preserving multi-disease simultaneous diagnosis scheme over medical records with multiple labels. Finally, the authors conclude the monograph and discuss future research directions of privacy-preserving e-Healthcare services in Chapter 7.
This book investigates data security approaches in Heterogeneous Communications Networks (HCN). First, the book discusses the urgent need for a decentralized data management architecture in HCN. The book investigates preliminaries and related research to help readers obtain a comprehensive picture of the research topic. Second, the book presents three blockchain-based approaches for data management in HCN: data provenance, data query, and data marketing. Finally, based on the insights and experiences from the presented approaches, the book discusses future research directions.
This book investigates decentralized trust-based privacy-preserving solutions in smart cities. The authors first present an overview of smart cities and privacy challenges and discuss the benefits of adopting decentralized trust models in achieving privacy preservation. The authors then give a comprehensive review of fundamental decentralized techniques and privacy-preserving cryptographic techniques. The next four chapters each detail a decentralized trust-based scheme, focusing respectively on privacy-preserving identity management, cross-domain authentication, data analytics, and data search, in specific use cases. Finally, the book explores open issues and outlines future research directions in the field of decentralized privacy preservation.
This book shares valuable insights into high-efficiency data transmission scheduling and into a group intelligent search and rescue approach for artificial intelligence (AI)-powered maritime networks. Its goal is to highlight major research directions and topics that are critical for those who are interested in maritime communication networks, equipping them to carry out further research in this field.The authors begin with a historical overview and address the marine business, emerging technologies, and the shortcomings of current network architectures (coverage, connectivity, reliability, etc.). In turn, they introduce a heterogeneous space/air/sea/ground maritime communication network architecture and investigate the transmission scheduling problem in maritime communication networks, together with solutions based on deep reinforcement learning. To accommodate the computation demands of maritime communication services, the authors propose a multi-vessel offloadingalgorithm for maritime mobile edge computing networks. In closing, they discuss the applications of swarm intelligence in maritime search and rescue.
This book introduces the Internet access for vehicles as well as novel communication and computing paradigms based on the Internet of vehicles. To enable efficient and reliable Internet connection for mobile vehicle users, this book first introduces analytical modelling methods for the practical vehicle-to-roadside (V2R) Internet access procedure, and employ the interworking of V2R and vehicle-to-vehicle (V2V) to improve the network performance for a variety of automotive applications. In addition, the wireless link performance between a vehicle and an Internet access station is investigated, and a machine learning based algorithm is proposed to improve the link throughout by selecting an efficient modulation and coding scheme.This book also investigates the distributed machine learning algorithms over the Internet access of vehicles. A novel broadcasting scheme is designed to intelligently adjust the training users that are involved in the iteration rounds for an asynchronous federated learning scheme, which is shown to greatly improve the training efficiency. This book conducts the fully asynchronous machine learning evaluations among vehicle users that can utilize the opportunistic V2R communication to train machine learning models. Researchers and advanced-level students who focus on vehicular networks, industrial entities for internet of vehicles providers, government agencies target on transportation system and road management will find this book useful as reference. Network device manufacturers and network operators will also want to purchase this book.
This SpringerBrief evaluates the cooperative effort of sensor nodes to accomplish high-level tasks with sensing, data processing and communication. The metrics of network-wide convergence, unbiasedness, consistency and optimality are discussed through network topology, distributed estimation algorithms and consensus strategy. Systematic analysis reveals that proper deployment of sensor nodes and a small number of low-cost relays (without sensing function) can speed up the information fusion and thus improve the estimation capability of wireless sensor networks (WSNs). This brief also investigates the spatial distribution of sensor nodes and basic scalable estimation algorithms, the consensus-based estimation capability for a class of relay assisted sensor networks with asymmetric communication topology, and the problem of filter design for mobile target tracking over WSNs. From the system perspective, the network topology is closely related to the capability and efficiency of network-wide scalable distributed estimation. Wireless Sensor Networks: Distributed Consensus Estimation is a valuable resource for researchers and professionals working in wireless communications, networks and distributed computing. Advanced-level students studying computer science and electrical engineering will also find the content helpful.
This book provides a comprehensive overview of wireless technologies for industrial network systems. The authors first describe the concept of industrial network systems and their application to industrial automation. They then go on to cover the role of sensing and control in industrial network systems, and the challenge of sensing and control in the industrial wireless environment. Then, the existing techniques for resource efficiency information transmission are introduced and studied. Afterward, the authors introduce sensing and control-oriented transmission for industrial network systems, which take advantage of spatial diversity gain to overcome the interference and fading, which in turn improves the transmission reliability without expending extra spectrum resources and enlarging the transmission delay. Subsequently, edge assisted efficient transmission schemes are introduced, which integrate the capacities of communication, computing, and control to relieve the contradiction ofresource limitation and massive data. Finally, the authors discuss open research issues and future works about information transmission in industrial network systems.
This book provides a comprehensive overview of data security in cloud storage, ranging from basic paradigms and principles, to typical security issues and practical security solutions. It also illustrates how malicious attackers benefit from the compromised security of outsourced data in cloud storage and how attacks work in real situations, together with the countermeasures used to ensure the security of outsourced data. Furthermore, the book introduces a number of emerging technologies that hold considerable potential - for example, blockchain, trusted execution environment, and indistinguishability obfuscation - and outlines open issues and future research directions in cloud storage security.
The topics addressed are important for the academic community, but are also crucial for industry, since cloud storage has become a fundamental component in many applications. The book offers a general introduction for interested readers with a basic modern cryptography background, and a reference guide for researchers and practitioners in the fields of data security and cloud storage. It will also help developers and engineers understand why some current systems are insecure and inefficient, and move them to design and develop improved systems.
This book investigates intelligent network resource management for IoV, with the objective of maximizing the communication and computing performance of vehicle users. Focusing on two representative use cases in IoV, i.e., safety message broadcast and autonomous driving, the authors propose link-layer protocol design and application-layer computing task scheduling to achieve the objective given the unique characteristics and requirements of IoV. In particular, this book illustrates the challenges of resource management for IoV due to network dynamics, such as time-varying traffic intensity and vehicle mobility, and presents intelligent resource management solutions to adapt to the network dynamics. The Internet of Vehicles (IoV) enables vehicle-to-everything connectivity and supports a variety of applications for vehicles on the road.Intelligent resource management is critical for satisfying demanding communication and computing requirements on IoV, while the highly dynamic network environments pose challenges to the design of resource management schemes. This book provides insights into the significance of adaptive resource management in improving the performance of IoV. The customized communication protocol and computing scheduling scheme are designed accordingly by taking the network dynamics information as an integral design factor. Moreover, the decentralized designs of the proposed solutions guarantee low signaling overhead and high scalability.
A comprehensive literature review summarizing recent resource management schemes in IoV, followed by the customized design of communication and computing solutions for the two IoV use cases is included which can serve as a useful reference for professionals from both academia and industry in the area of IoV and resource management. Researchers working within this field and computer science and electrical engineering students will find this book useful as well.
This book introduces human reconstruction technologies in smart homes leveraging mmWave signals. It begins by presenting the overview of human reconstruction and the development of mmWave sensing technology. The authors introduce a mmWave sensing-based human posture reconstruction approach, which exploits mmWave signals to sense and track multiple users’ postures as they move, walk or sit. It also presents a facial expression reconstruction system that reconstructs 3D human faces and continuously exhibits facial expressions using mmWave. The authors describe a hand gesture reconstruction system that utilizes mmWave signals to generate 3D hand skeletons and reconstruct hand meshes. A thorough investigation of state-of-art research work is further presented covering human reconstruction, mmWave sensing and mmWave-based human reconstruction. Finally, conclusions and the direction of future research are highlighted for this book.
Human and the cyberworld are moving towards high synchronization as more IoT devices are integrated in smart homes. By reconstructing human postures, facial expressions, and hand gestures in the cyberworld, a virtual human avatar can map the state of human into the physical world and deeply integrate reality and virtuality. The process strongly energizes emerging applications such as virtual reality, augmented reality, meta-universe, immersive games, etc.
This book targets graduate-level students majoring in the computer science and engineering, and electrical engineering. Professionals working in wireless signal-based human sensing will also find this book a valuable resource.
This book proposes secure schemes to address security challenges in secure automatic dependent surveillance-broadcast systems (ADS-B) from five different angles. First, the authors examine encryption schemes applied to the ADS-B environment for protecting messages confidentiality. Second, they propose an ADS-B broadcast authentication scheme with batch verification by employing an identity-based signature. Third, they present ADS-B broadcast authentication scheme based on a digital signature with message recovery, which provides a feature that the message is recoverable from the signature. Fourth, they propose a new cryptographic solution to ADS-B security. Finally, they propose an accurate and efficient cognitive aircraft location verification scheme preserving aircraft location privacy by utilizing a grid-based k-nearest neighbor algorithm. In summary, the authors show how ADS-B data links can greatly enhance flight safety by these proposed schemes without sacrificing data security.Proposes several secure schemes to address security challenges in secure automatic dependent surveillance-broadcast systems (ADS-B);Provides extensive experiments and evaluates the proposed schemes using real-world data;Shows how ADS-B data links can greatly enhance safety without sacrificing data security
This monograph addresses the spectrum-scarcity problem by providing a comprehensive overview of spectrum resource management in Cognitive Radio Sensor Networks (CRSNs). It shows a variety of CRSN applications covering Machine-to-Machine communications, cyber physical systems and Internet-of-Things. The authors explore the benefits of an integrated energy efficient spectrum management solution for CRSNs including spectrum sensing, decision and allocation. Both theoretical and experimental aspects of CRSNs are covered in detail.
Academics, researchers and developers will find this monograph an exceptional resource with valuable knowledge and insights. It also has extensive references from top journals, conference proceedings, books and standards.
