The new trends in networking: IoT, 5G, and cognitive radio

The domain of networking and wireless communication is rapidly expanding to the point where traditional legacy networks research is nearly complete, and they are supposed to be an elder. IoT, the Internet of Things, and the 5G radio communications are the newest networking advancements. These two technologies fulfil all of the researchers' goals of improving people's quality of life. IoT is a framework that allows everyday devices to become smarter, processing to become more intelligent, and communication to become more relevant. The Internet of Things (IoT) has already made huge progress as a ubiquitous solution platform for the linked world. We also discussed the Radio Cognitive RC, which allows people to connect to networks as secondary users at no cost while the service provided is not as good as that provided to primary users who pay a license to use the network. RC can provide a solution for best-effort IoT applications that do not require constant connectivity and high QoS requirements. This study describes all of these technologies and concludes with a recommendation for using IoT and RC in our further works.

The Internet of Things (IoT) concept is evolving rapidly and influencing new developments in various application domains, such as the Internet of Mobile Things (IoMT), Autonomous Internet of Things (A-IoT), Autonomous System of Things (ASoT), Internet of Autonomous Things (IoAT), Internet of Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc. that are progressing/advancing by using IoT technology. The IoT influence represents new development and deployment challenges in different areas such as seamless platform integration, context based cognitive network integration, new mobile sensor/actuator network paradigms, things identification (addressing, naming in IoT) and dynamic things discoverability and many others. The IoRT represents new convergence challenges and their need 98to be addressed, in one side the programmability and the communication of multiple heterogeneous mobile/autonomous/robotic things for cooperating, their coordination, configuration, exchange of information, security, safety and protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrency require new ideas for integrating the intelligent “devices”, collaborative robots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing, self-repair of resources, changing resource state, (re-) configuration and context based IoT systems for service implementation and integration with IoT network service composition are of paramount importance when new “cognitive devices” are becoming active participants in IoT applications. This chapter aims to be an overview of the IoRT concept, technologies, architectures and applications and to provide a comprehensive coverage of future challenges, developments and applications.

This article proposes deep learning (DL) framework constructed using deep autoencoder (DAE) to detect the malicious nodes in an Internet of Things (IoT) network assisted by the cognitive radio (CR) technology. In the IoT era, a plethora of nodes are connected to the network for the purpose of collecting and exchanging data. CR technology finds its role in IoT applications because of its ability to efficiently exploit the available spectrum. In this article, we consider IoT nodes as secondary users that perform cooperative spectrum sensing (CSS). Specifically, these IoT nodes sense the spectrum and send their reports to the fusion center (FC) to determine whether the spectrum is occupied by the primary user or not. In such a scenario, the existence of malicious IoT nodes might mislead the FC. To determine which of these IoT nodes are benevolent and which are malicious is crucial. We adopt a DAE-based DL framework, called DAE-TRUST, to detect malicious nodes in CR-assisted IoT. The proposed DAE-TRUST is able to identify the malicious nodes, whose reports can be excluded from the spectrum detection process. Simulation results, in six different real-world environments, show that our DAE-TRUST enhances the performance of CSS in IoT applications.

The Internet of things (IoT) idea is advancing quickly and affecting new advancements in different application areas. For example, the Internet of mobile things (IoMT), autonomous Internet of things (An IoT), autonomous system of things (ASoT), Internet of autonomous things (IoAT), Internet of things clouds (IoT-C) and the Internet of robotic things (IoRT) that are regressing/progressing by utilizing IoT innovation. The IoRT speaks to new assembly challenges, and there should be tended to, in one surface the programmability and correspondence of various heterogeneous versatile/self-ruling/mechanical things for participating, their coordination, set up, trade of data, security, well-being and insurance. Advancements in IoT heterogeneous equal preparing/correspondence and dynamic frameworks dependent on parallelism and simultaneousness require new thoughts for coordinating the astute “gadgets”, community robots (COBOTS) and keen on IoT appliance. Dynamic viability, identity mending, self-fix of assets, varying asset condition system and setting support IoT frameworks. Administration usage and reconciliation through IoT organize administration creation are of vital significance when original “intellectual gadgets” are turning out to be dynamic members in IoT applications.

Internet of things (IoT) has changed human lifestyle by introducing various smart applications. In recent years, sophisticated automation systems have become an essential outcome of the IoT paradigm. Due to the characteristics of IoT applications, devices need to communicate with each other seamlessly. New networking technologies and architectures have also been designed to support the communication requirements of current and future IoT devices. Wireless and radio communications are very desirable for achieving communication among the devices with various proximity. As there is a rapid growth in the number of IoT devices networked based on wireless transmission, radio frequency resource needs to be allocated efficiently to enhance radio spectrum utilization. In wireless connection, Cognitive Radio (CR) is an opportunistic radio access technology targeted to improve the spectrum usage and to mitigate the excessive contention of radio communication. In this chapter, we have identified the functional similarities between IoT and CR, and the challenges that are important to be addressed to integrate CR technology for IoT. We have also proposed a framework for cognitive radio enabled IoT that provides efficient radio spectrum utilization for IoT.

Internet of Things (IoT) is a new challenging paradigm for connecting a variety of heterogeneous networks. Since its introduction, many researchers have been studying how to efficiently exploit and manage spectrum resource for IoT applications. An explosive increase in the number of IoT devices accelerates towards the future-connected society but yields a high system complexity. Cognitive radio (CR) technology is also a promising candidate for future wireless communications. CR via dynamic spectrum access provides opportunities to secondary users (SUs) to access licensed spectrum bands without interfering primary users by performing spectrum sensing before accessing available spectrum bands. However, multipath effects can degrade the sensing capability of an individual SU. Therefore, for more precise sensing, it is helpful to exploit multiple collaborative sensing users. The main problem in cooperative spectrum sensing is the presence of inaccurate sensing information received from the multipath-affected SUs and malicious users at a fusion center (FC). In this paper, we propose a genetic algorithm-based soft decision fusion scheme to determine the optimum weighting coefficient vector against SUs’ sensing information. The weighting coefficient vector is further utilized in a soft decision rule at FC in order to make a global decision. Through extensive simulations, the effectiveness of the proposed scheme is evaluated compared with other conventional schemes.

Wireless Sensor Networks (WSNs) can be termed as an auto-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure and motion etc. WSNs may comprise thousands of Internet of Things (IoT) devices to sense and collect data from its surrounding, process the data and take an automated and mechanized decision. On the other side the proliferation of these devices will soon cause radio spectrum shortage. So, to facilitate these networks, we integrate Cognitive Radio (CR) functionality in these networks. CR can sense the unutilized spectrum of licensed users and then use these empty bands when required. In order to keep the IoT nodes functional all time, continuous energy is required. For this reason the energy harvested techniques are preferred in IoT networks. Mainly it is preferred to harvest Radio Frequency (RF) energy in the network. In this paper a region based multi-channel architecture is proposed. In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region. The Secondary User (SU) that are the licensed user is IoT enabled with Cognitive Radio (CR) techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy. To harvest energy efficiently and to reduce the energy consumption during sensing, the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel. From the experimental analysis, it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel. We also show that channel load can be highly reduced and channel utilization is proved to be more proficient. Thus, this proves the proposed architecture cost-effective and energy-efficient.

Energy efficient wireless communication technique based on Cognitive Radio for Internet of Things

Sixth-generation (6G) wireless communications and networks will continue to move to higher frequency and wider bandwidth, with much higher data rate and spectral efficiency. Given the heterogeneity and densification of Internet of Things (IoT), 6G wireless network may need to be extended to modern random access (RA) for IoT applications, which can be achieved via smart protocol design and advanced signal processing and communications technologies. The modern RA techniques, such as massive multiple-input–multiple-output (MIMO), OFDMA, nonorthogonal multiple access (NOMA), sparse signal processing, or new orthogonal design techniques provide good candidacy for 6G-enabled IoT. In 6G, grant-free transmission should be designed for distributed IoT applications. IoT applications are often involved in self-organizing decision making. 6G-enabled IoT will take advantage of the recent development of artificial intelligence (AI) techniques. It will generate new knowledge and understanding and accelerate discovery and innovation in IoT. Each of these efforts is designed to amplify the intrinsically multidisciplinary nature of the emerging field of IoT. The 6G-enabled IoT will establish theoretical, technical, and ethical frameworks that will be applied to tackle many challenges in IoT, advancing technology for humanity.

CR-IoTNet: Machine learning based joint spectrum sensing and allocation for cognitive radio enabled IoT cellular networks

Various global development opportunities have been escalated through the Internet of Everything (IoE) with the potential of progressing Sustainable Development goals - dramatically accelerating and improving lives of millions. The emerging economies of developing countries with minimal investments have crafted a huge array of (IoE) technologies strongly demanding interoperability and interconnectivity that are affordable, scalable and available, significantly improving people's quality of life. Growing number of devices requiring interconnectivity referring to the concept of (IoE) headed beyond sensors, chips, computers and smartphones. The modern replete technology has enabled both synchronous and asynchronous communication without human interaction in many industrial processes, fleet management, stock exchanges, inventory systems and environment monitoring regardless of their extensive deployment. Information Communication Technology (ICT) is a fast evolving industry in developing countries, offering (IoE)'s huge potential of transformation and disruption. The global development challenges have emphasised the need for communication and due to (IoE) advancements, long-standing issues (health care, stock, management, cross-border, technology diffusion etc.) would be surmounted in an affordable and quick manner. The developing countries would turn-around with the help of a long-awaited (IoE) technology aiming at improving their economies and lives of millions of people. The key to increased usage is the interconnectedness of diverse range of devices which formerly were incompatible with each other. The interoperability between devices has rendered (IoE) both practical and possible and in accordance with the international communication standards. Research and industrial organisations have stipulated the formation of a hyper-connected society where tens of billions daily life objects and devices would communicate, forming a global network of smart devices. The successful provision of intelligent and smart devices through (IoE) services leads to challenging security concerns especially in developing countries where communication and devices are cheap but there is a lack of secure (IoE) infrastructures. The current paper would envisage a secure architecture for diversely connected objects within developing countries. A secure configuration methodology of the bootstrapping scheme is proposed as a solution in this paper. The bootstrapping scheme is activated as soon as a new object get connected to an operational network. This method is feasible to secure the devices and avoid data exploitation within developing countries where communication across devices is still lacking protected infrastructures. A review of the Internet of Everything (IoE) is represented beneath, along with a brief portrayal of the applications and difficulties confronted by the (IoE).

<abstract> <p>The Internet of Things (IoT) is considered an effective wireless communication, where the main challenge is to manage energy efficiency, especially in cognitive networks. The data communication protocol is a broadly used approach in a wireless network based IoT. Cognitive Radio (CR) networks are mainly concentrated on battery-powered devices for highly utilizing the data regarding the spectrum and routing allocation, dynamic spectrum access, and spectrum sharing. Data aggregation and clustering are the best solutions for enhancing the energy efficiency of the network. Most researchers have focused on solving the problems related to Cognitive Radio Sensor Networks (CRSNs) in terms of Spectrum allocation, Quality of Service (QoS) optimization, delay reduction, and so on. However, a very small amount of research work has focused on energy restriction problems by using the switching and channel sensing mechanism. As this energy validation is highly challenging due to dependencies on various factors like scheduling priority to the registered users, the data loss rate of unlicensed channels, and the possibilities of accessing licensed channels. Many IoT-based models involve energy-constrained devices and data aggregation along with certain optimization approaches for improving utilization. In this paper, the cognitive radio framework is developed for medical data transmission over the Internet of Medical Things (IoMT) network. The energy-efficient cluster-based data transmission is done through cluster head selection using the hybrid optimization algorithm named Spreading Rate-based Coronavirus Herding-Grey Wolf Optimization (SR-CHGWO). The network lifetime is improved with a cognitive- routing based on IoT framework to enhance the efficiency of the data transmission through the multi-objective function. This multi-objective function is derived using constraints like energy, throughput, data rate, node power, and outage probability delay of the proposed framework. The simulation experiments show that the developed framework enhances the energy efficiency using the proposed algorithm when compared to the conventional techniques.</p> </abstract>

The Internet of Things (IoT) is a promising subject of technical, social, and economic implication. The primary aspect of IoT is different objects are being combined with internet connectivity with powerful data analytic capabilities. The concept IoT is all about connecting various devices and sensors to the internet i.e. IoT is a world wide network of interconnected objects, but it is not always palpable how to provide the inter connectivity. On the basis of some studies, it is seen that the impact of IoT on the internet and economy are very inspiring which includes great global economic impact by next few years. IoT is capable to establish interconnectivity of objects through mainly, wireless communication technologies as cost-effectiveness issues and accessibility to remote users make wireless communication as a feasible solution but IoT paradigm pretenses new challenges to the communication technology as several objects of heterogeneous in nature will need to be connected and one of the major challenge is the scarcity of available spectrum to establish the connectivity. To address these issues new radio technologies and network architectures need to be thought of to accommodate several future devices having connectivity demands and consequently trends are shifting to the network which is intelligent enough to adapt with the ambience i.e. Cognitive Radio(CR) Networks and introduction of CR into IoT can improve the efficiency of the spectrum. This paper explores the possibility to put forward the application prospect of the cognitive radio-based platform into IoT.

In concert with advances of wireless technologies in facilitating internet connectivity of Internet of Things (IoT) devices, mobile edge computing can provision and distribute computing resources at the cloudlets to efficiently process a high volume of IoT data. Among the IoT applications, multi-party data sharing among IoT devices, wireless access nodes and cloudlets is becoming increasingly critical, not only because the data collected by each single IoT device will often stay unmined, but also because of the security concern. As IoT applications' dependence on the cloud environment grows, the rich resources at cloudlets often become the attack targets, and the IoT data that are stored or processed using the cloud resources will be jeopardized. For the internet of important things, we have investigated how to efficiently and securely share the data among multi-party. In particular, for a group of cooperative IoT devices, by leveraging the cloud resources available at the wireless access points, a secure cache site with fast data uploading rate is chosen for each user. To minimize the overall data downloading time, the multi-party multi-path data delivery scheme is also designed such that each user can efficiently retrieve the data belonging to other parties.

Both the internet-connected devices, i.e. IoT and Cognitive Radio Network (CRN) are considered to be the future technologies for the fifth generation of cellular wireless standards (5G). On the one hand, Internet of Things (IoT) focuses primarily on how to allow general objects to see, hear, and smell their own physical environment and make them connected to share the observations. On the other hand, a CRN is based on a complex spectrum allocation system, and licenced primary users (PUs) or unlicenced secondary users (SUs) are allowed to share the spectrum, provided they do not cause significant interference. The IoTs are meaningless if IoT objects are not equipped with cognitive radio capability. In cognitive radio, it is important to control the transmission power of SUs so that the interference should not be harmful to the quality of service of PUs. In this paper, the authors addressed the effects of imperfect power control between primary users (PUs) and the secondary users (SUs) of an IoT-based CRN. The effect of the co-channel interference (CCI) and adjacent channel interferences (ACIs) occurring in CRN using MC-CDMA system is also analysed. A new expression of the signal-to-interference-noise ratio (SINR) for CRN-based MC-CDMA system over a Nakagami-[Formula: see text] fading channel with imperfect power control condition is derived and investigated. The performance of IoT-based CRN using MC-CDMA system over the frequency selective multipath fading channel is examined with varying the number of users, the SINR per bit, number of fading path and number of sub-carriers. From the simulation results, we have seen that the SINR performance is affected by these parameters. The result of the analysis will provide relevant information to design the physical layer protocol for high-speed IoT-based CRN system for 5G.