Xiaoshuang Xing

Bio: Xiaoshuang Xing is an academic researcher from Changshu Institute of Technology. The author has contributed to research in topics: Cognitive radio & Computer science. The author has an hindex of 12, co-authored 49 publications receiving 1142 citations. Previous affiliations of Xiaoshuang Xing include Soochow University (Suzhou) & George Washington University.

Spectrum prediction in cognitive radio networks

Abstract: Spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility are four major functions of cognitive radio systems. Spectrum sensing is utilized to observe the spectrum occupancy status and recognize the channel availability, while CR users dynamically access the available channels through the regulation processes of spectrum decision, spectrum sharing, and spectrum mobility. To alleviate the processing delays involved in these four functions and to improve the efficiency of spectrum utilization, spectrum prediction for cognitive radio networks has been extensively studied in the literature. This article surveys the state of the art of spectrum prediction in cognitive radio networks. We summarize the major spectrum prediction techniques, illustrate their applications, and present the relevant open research challenges.

A Privacy Preserving Communication Protocol for IoT Applications in Smart Homes

Abstract: The development of the Internet of Things has made extraordinary progress in recent years in both academic and industrial fields There are quite a few smart home systems (SHSs) that have been developed by major companies to achieve home automation However, the nature of smart homes inevitably raises security and privacy concerns In this paper, we propose an improved energy-efficient, secure, and privacy-preserving communication protocol for the SHSs In our proposed scheme, data transmissions within the SHS are secured by a symmetric encryption scheme with secret keys being generated by chaotic systems Meanwhile, we incorporate message authentication codes to our scheme to guarantee data integrity and authenticity We also provide detailed security analysis and performance evaluation in comparison with our previous work in terms of computational complexity, memory cost, and communication overhead

A Privacy Preserving Communication Protocol for IoT Applications in Smart Homes

Abstract: Internet of things is the trending direction when it comes to designing smart living environment. One of the popular applications of Internet of things is the smart home system. A smart home system usually consists of various types of connected sensors, actuators, appliances and a controller. The controller analyzes the data reported by the sensors and sends out messages to electric appliances and other sensors to ask them to behave accordingly. There are a lot of smart home designs proposed in the literature to make the systems smarter and more comfortable. However, little work has considered the security and privacy issues in smart home systems. In this paper, we analyze the differences of security and privacy issues that lie in the smart home systems, smart grid, and wireless sensor networks. Further, we propose our own solutions that achieves privacy preservation during the communications between end sensors and appliances and the controller.

An Attribute-Based Encryption Scheme to Secure Fog Communications

Abstract: Fog computing is deemed as a highly virtualized paradigm that can enable computing at the Internet of Things devices, residing in the edge of the network, for the purpose of delivering services and applications more efficiently and effectively Since fog computing originates from and is a non-trivial extension of cloud computing, it inherits many security and privacy challenges of cloud computing, causing the extensive concerns in the research community To enable authentic and confidential communications among a group of fog nodes, in this paper, we propose an efficient key exchange protocol based on ciphertext-policy attribute-based encryption (CP-ABE) to establish secure communications among the participants To achieve confidentiality, authentication, verifiability, and access control, we combine CP-ABE and digital signature techniques We analyze the efficiency of our protocol in terms of security and performance We also implement our protocol and compare it with the certificate-based scheme to illustrate its feasibility

Channel quality prediction based on Bayesian inference in cognitive radio networks

Abstract: The problem of channel quality prediction in cognitive radio networks is investigated in this paper. First, the spectrum sensing process is modeled as a Non-Stationary Hidden Markov Model (NSHMM), which captures the fact that the channel state transition probability is a function of the time interval the primary user has stayed in the current state. Then the model parameters, which carry the information about the expected duration of the channel states and the spectrum sensing accuracy (detection accuracy and false alarm probability) of the SU, are estimated via Bayesian inference with Gibbs sampling. Finally, the estimated NSHMM parameters are employed to design a channel quality metric according to the predicted channel idle duration and spectrum sensing accuracy. Extensive simulation study has been performed to investigate the effectiveness of our design. The results indicate that channel ranking based on the proposed channel quality prediction mechanism captures the idle state duration of the channel and the spectrum sensing accuracy of the SUs, and provides more high quality transmission opportunities and higher successful transmission rates at shorter spectrum waiting times for dynamic spectrum access.

Literature review of Industry 4.0 and related technologies

Abstract: Manufacturing industry profoundly impact economic and societal progress. As being a commonly accepted term for research centers and universities, the Industry 4.0 initiative has received a splendid attention of the business and research community. Although the idea is not new and was on the agenda of academic research in many years with different perceptions, the term “Industry 4.0” is just launched and well accepted to some extend not only in academic life but also in the industrial society as well. While academic research focuses on understanding and defining the concept and trying to develop related systems, business models and respective methodologies, industry, on the other hand, focuses its attention on the change of industrial machine suits and intelligent products as well as potential customers on this progress. It is therefore important for the companies to primarily understand the features and content of the Industry 4.0 for potential transformation from machine dominant manufacturing to digital manufacturing. In order to achieve a successful transformation, they should clearly review their positions and respective potentials against basic requirements set forward for Industry 4.0 standard. This will allow them to generate a well-defined road map. There has been several approaches and discussions going on along this line, a several road maps are already proposed. Some of those are reviewed in this paper. However, the literature clearly indicates the lack of respective assessment methodologies. Since the implementation and applications of related theorems and definitions outlined for the 4th industrial revolution is not mature enough for most of the reel life implementations, a systematic approach for making respective assessments and evaluations seems to be urgently required for those who are intending to speed this transformation up. It is now main responsibility of the research community to developed technological infrastructure with physical systems, management models, business models as well as some well-defined Industry 4.0 scenarios in order to make the life for the practitioners easy. It is estimated by the experts that the Industry 4.0 and related progress along this line will have an enormous effect on social life. As outlined in the introduction, some social transformation is also expected. It is assumed that the robots will be more dominant in manufacturing, implanted technologies, cooperating and coordinating machines, self-decision-making systems, autonom problem solvers, learning machines, 3D printing etc. will dominate the production process. Wearable internet, big data analysis, sensor based life, smart city implementations or similar applications will be the main concern of the community. This social transformation will naturally trigger the manufacturing society to improve their manufacturing suits to cope with the customer requirements and sustain competitive advantage. A summary of the potential progress along this line is reviewed in introduction of the paper. It is so obvious that the future manufacturing systems will have a different vision composed of products, intelligence, communications and information network. This will bring about new business models to be dominant in industrial life. Another important issue to take into account is that the time span of this so-called revolution will be so short triggering a continues transformation process to yield some new industrial areas to emerge. This clearly puts a big pressure on manufacturers to learn, understand, design and implement the transformation process. Since the main motivation for finding the best way to follow this transformation, a comprehensive literature review will generate a remarkable support. This paper presents such a review for highlighting the progress and aims to help improve the awareness on the best experiences. It is intended to provide a clear idea for those wishing to generate a road map for digitizing the respective manufacturing suits. By presenting this review it is also intended to provide a hands-on library of Industry 4.0 to both academics as well as industrial practitioners. The top 100 headings, abstracts and key words (i.e. a total of 619 publications of any kind) for each search term were independently analyzed in order to ensure the reliability of the review process. Note that, this exhaustive literature review provides a concrete definition of Industry 4.0 and defines its six design principles such as interoperability, virtualization, local, real-time talent, service orientation and modularity. It seems that these principles have taken the attention of the scientists to carry out more variety of research on the subject and to develop implementable and appropriate scenarios. A comprehensive taxonomy of Industry 4.0 can also be developed through analyzing the results of this review.

An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges

Abstract: The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of Internet of Things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the agriculture sector. There is a paradigm shift from use of wireless sensor network (WSN) as a major driver of smart agriculture to the use of IoT and DA. The IoT integrates several existing technologies, such as WSN, radio frequency identification, cloud computing, middleware systems, and end-user applications. In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. Furthermore, we provide future trends and opportunities which are categorized into technological innovations, application scenarios, business, and marketability.

A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures

Abstract: The Internet of Things (IoT) is the next era of communication. Using the IoT, physical objects can be empowered to create, receive, and exchange data in a seamless manner. Various IoT applications focus on automating different tasks and are trying to empower the inanimate physical objects to act without any human intervention. The existing and upcoming IoT applications are highly promising to increase the level of comfort, efficiency, and automation for the users. To be able to implement such a world in an ever-growing fashion requires high security, privacy, authentication, and recovery from attacks. In this regard, it is imperative to make the required changes in the architecture of the IoT applications for achieving end-to-end secure IoT environments. In this paper, a detailed review of the security-related challenges and sources of threat in the IoT applications is presented. After discussing the security issues, various emerging and existing technologies focused on achieving a high degree of trust in the IoT applications are discussed. Four different technologies, blockchain, fog computing, edge computing, and machine learning, to increase the level of security in IoT are discussed.

Securing Fog Computing for Internet of Things Applications: Challenges and Solutions

Abstract: Internet of Things (IoT) allows billions of physical objects to be connected to collect and exchange data for offering various applications, such as environmental monitoring, infrastructure management, and home automation. On the other hand, IoT has unsupported features (e.g., low latency, location awareness, and geographic distribution) that are critical for some IoT applications, including smart traffic lights, home energy management and augmented reality. To support these features, fog computing is integrated into IoT to extend computing, storage and networking resources to the network edge. Unfortunately, it is confronted with various security and privacy risks, which raise serious concerns towards users. In this survey, we review the architecture and features of fog computing and study critical roles of fog nodes, including real-time services, transient storage, data dissemination and decentralized computation. We also examine fog-assisted IoT applications based on different roles of fog nodes. Then, we present security and privacy threats towards IoT applications and discuss the security and privacy requirements in fog computing. Further, we demonstrate potential challenges to secure fog computing and review the state-of-the-art solutions used to address security and privacy issues in fog computing for IoT applications. Finally, by defining several open research issues, it is expected to draw more attention and efforts into this new architecture.