The blockchain: State-of-the-art and research challenges

Cognitive radio (CR)-based Internet of Things (IoT) system is an effective step toward a world of smart technology. Many frameworks have been proposed to build CR-based IoT systems. The CR-based IoT frameworks are the key points on which this survey focuses. Efficient spectrum sensing and sharing are the main functional components of the CR-based IoT. Reviews of recent SS and sharing approaches are presented in this survey. This survey classifies the SS and sharing approaches and discusses the merits and limitations of those approaches. Moreover, this survey discusses the design factors of the CR-based IoT and the criteria by which the proper SS and access approaches are selected. Furthermore, the survey explores the integration of newly emerging technologies with the CR-based IoT systems. Finally, the survey highlights some emerging challenges and concludes with suggesting future research directions and open issues.

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Technical Issues on Cognitive Radio-Based Internet of Things Systems: A Survey

In recent years, the growing number of devices connected to the internet has increased significantly. These devices can interact with the external environment and with human beings through a wide range of sensors that, perceiving reality through the digitization of some parameters of interest, can provide an enormous amount of data. All this data is then shared on the network with other devices and with different applications and infrastructures. This dynamic and ever-changing world underlies the Internet of Things (IoT) paradigm. To date, countless applications based on IoT have been developed; think of Smart Cities, smart roads, and smart industries. This article analyzes the current architectures, technologies, protocols, and applications that characterize the paradigm.

https://www.mdpi.com/2078-2489/12/2/87/pdf

Internet of things: A general overview between architectures, protocols and applications

Internet of Vehicles is a specific application of Internet of Things technology in intelligent transportation systems, and has attracted attention of relevant research institutions, automobile manufacturers and communication technology suppliers all over the world. The US government has spent hundreds of millions of dollars on DSRC development, which is a technology that can help achieve V2V and V2I communications, and enable vehicles to communicate with intelligent traffic lights to mitigate traffic congestion and accidents or bad weather on the road. Automakers such as GM and Toyota have well deployed Wi-Fi-based DSRC technology. But with the continuous development of 5G and D2D communications, cellular technology tends to be a strong candidate for V2X communications..Although 5G communication technology does not yet have a unified standard, its related concepts and trends have been recognized by industry area. Automobile manufacturers represented by Ford and BMW expect to achieve a leap in automotive networking through 5G. In the face of the 5G era, the dispute between DSRC and LTE standards has become a hot topic in the field of car networking. DSRC, a dedicated short-range communication developed and tested by automotive technology suppliers is under threat, and the next generation of 5G technology might be the final answer. Based on this point, this paper firstly introduces the development history of the Internet of Vehicles communication standard, and analyzes the advantages and disadvantages of DSRC and cellular network communication technology. Then, the three core elements of the Internet of Vehicles (Node Performance, local Network, and Internet of Things) are discussed for the development trend of vehicle networking communication technology in the context of 5G. Finally, this chapter explains the impact of the development of 5G communication technology on the future development of vehicle networking, and proposes the possible development directions of future vehicle networking technologies.

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Emerging Technologies for 5G-Enabled Vehicular Networks

Blockchain technology has recently inspired remarkable attention due to its unique features, such as privacy, accountability, immutability, and anonymity, to name of the few. In contrast, core functionalities of most Internet of Things (IoT) resources make them vulnerable to security threats. The IoT devices, such as smartphones and tablets, have limited capacity in terms of network, computing, and storage, which make them easier for vulnerable threats. Furthermore, a massive amount of data produced by the IoT devices, which is still an open challenge for the existing platforms to process, analyze, and unearth underlying patterns to provide convenience environment. Therefore, a new solution is required to ensure data accountability, improve data privacy and accessibility, and extract hidden patterns and useful knowledge to provide adequate services. In this paper, we present a secure fitness framework that is based on an IoT-enabled blockchain network integrated with machine learning approaches. The proposed framework consists of two modules: a blockchain-based IoT network to provide security and integrity to sensing data as well as an enhanced smart contract enabled relationship and inference engine to discover hidden insights and useful knowledge from IoT and user device network data. The enhanced smart contract aims to support users with a practical application that provides real-time monitoring, control, easy access, and immutable logs of multiple devices that are deployed in several domains. The inference engine module aims to unearth underlying patterns and useful knowledge from IoT environment data, which helps in effective decision making to provide convenient services. For experimental analysis, we implement an intelligent fitness service that is based on an enhanced smart contract enabled relationship and inference engine as a case study where several IoT fitness devices are used to securely acquire user personalized fitness data. Furthermore, a real-time inference engine investigates user personalized data to discover useful knowledge and hidden insights. Based on inference engine knowledge, a recommendation model is developed to recommend a daily and monthly diet, as well as a workout plan for better and improved body shape. The recommendation model aims to facilitate a trainer formulating effective future decisions of trainee’s health in terms of a diet and workout plan. Lastly, for performance analysis, we have used Hyperledger Caliper to access the system performance in terms of latency, throughput, resource utilization, and varying orderer and peers nodes. The analysis results imply that the design architecture is applicable for resource-constrained IoT blockchain platform and it is extensible for different IoT scenarios.

https://www.mdpi.com/1424-8220/21/5/1640/pdf

Towards Secure Fitness Framework Based on IoT-Enabled Blockchain Network Integrated with Machine Learning Algorithms.

Internet of Things, cognitive systems, and blockchain technology are three fields which have created numerous revolutions in software development. It seems that a combination among these fields may results in emerging a high potential and interesting field. Therefore, in this paper, we propose a framework for Internet of Things based on cognitive systems and blockchain technology. To the best of our knowledge, there is no framework for Internet of Things based on cognitive systems and blockchain. In order to study the applicability of the proposed framework, a recommender system based on the proposed framework is suggested. Since the proposed framework is novel, the suggested recommender system is novel. The suggested recommender system is compared with the existing recommender systems. The results show that the suggested recommender system has several benefits which are not available in the existing recommender systems.

Kamran Gholizadeh

Papers

A framework for cognitive Internet of Things based on blockchain