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Intelligence in IoT-Based 5G Networks: Opportunities and Challenges
Abstract
The requirement of high data rates, low latency, efficient use of spectrum and coexistence of different network technologies are major considerations in Internet of Things (IoT) based Fifth Generation (5G) networks. To achieve the above requirements, the incorporation of Artificial Intelligence (AI) is required to make efficient decisions based on the massive data generated by the large number of IoT devices. AI methods analyse the data to extract the patterns and make sense of the data to prescribe action to the end devices. In this work, we first give an overview, discussing the challenges and relevant solutions of the 5G and IoT technologies including the IoT based 5G enabling technologies. Second, we discuss the need for AI in future IoT based 5G networks in the perspective of Kipling's method. In addition, we review the intelligent use of spectrum through full duplex and cognitive radio technologies.
... Javaid et al. [23] presented a firmware-based approach for integrating intelligence into IoT devices. The IoT-based 5G ecosystem depicted in Figure 15 enables the application of AI techniques to Big Data for prediction and real-time analysis. ...
... IoT-based 5G ecosystem[23]. ...
... Intelligent IoT-based 5G ecosystem[23]. ...
... On the other hand, there are some routing solutions implemented on the basis of reinforcement learning algorithms to solve the routing issues encountered in dynamic nature of CR enabled IoT networks [28,29]. Initially, one of the reinforcements learning technique, Q-learning is used for the spectrum aware routing of CR enabled IoT in [30]. ...
... The routing solutions presented in [15][16][17][18][19][20][21][22][23][24][25] and [26][27][28][29][30][31][32][33] do not consider the concept of multi-agent in taking the routing decisions and used a single agent assumption. Also, the concept of non-cooperative game theory is applied only in [28] and [29] for the routing decisions of SUs. ...
... The routing solutions presented in [15][16][17][18][19][20][21][22][23][24][25] and [26][27][28][29][30][31][32][33] do not consider the concept of multi-agent in taking the routing decisions and used a single agent assumption. Also, the concept of non-cooperative game theory is applied only in [28] and [29] for the routing decisions of SUs. The routing technique used in [29] needs to get the routing decisions of all SUs by sharing the information during routing. ...
Cognitive Radio Network (CRN) has turn up to solve the issue of spectrum congestion occurred due to the wide spread usage of wireless applications for 6G based Internet of Things (IoT) network. The Secondary Users (SUs) are allowed to access dynamically the frequency channels owned by the Primary Users (PUs). In this paper, we focus the matter of contention of routing in multi hops setup by the SUs for a known destination in the presence of PUs. The traffic model for routing is generated on the basis of Poison Process of Markov Model. Every SU requires to reduce the end-to-end delay and packet loss of its transmission simultaneously to improve the data rate for the Quality of Service (QoS) of the Secondary Users. The issue of routing is formulated as stochastic learning process of non-cooperative games for the transformation of routing decisions of SUs. We propose a distributed non-cooperated reinforcement learning based solution for solving the issue of dynamic routing that can avert user interferences and channel interferences between the competing Sus in 6G-IoT network. The proposed solution combines and simulate the results to show the effectiveness and working of the proposed solution in decreasing the end-to-end delay, packet loss while meeting the average data rate requirement of QoS for SUs.
... Nesnelerin İnterneti (IoT), internet aracılığıyla birbirine bağlı farklı nesnelerin, dünya çapındaki ağını kullanarak, gerçek dünyayı geliştirmek ve kontrol etmek için kullanılan modern bir teknolojidir [1]. İnternete bağlı milyarlarca akıllı nesneyi / cihazı ifade eder [2]. Bu akıllı nesneler, kuruldukları ağ içerisinde meydana gelen talepleri /sorunları / değişiklikleri tespit edip, takip edebilir ve elde edilen verileri karar destek sistemlerine ileterek hızlı ve doğru bir şekilde dinamik çözümler sunabilirler. ...
... Bilgi katmanında bu veriler, veri analitiği yoluyla anlamlı bilgilere dönüştürülür ve uygulama katmanı yoluyla son kullanıcıya sunulur [65]. IoT içerisindeki veri paylaşım kalitesi, bilgiyi paylaşan iki internet bağlantılı cihazı tanımlarken [66], zekâ, IoT'nin verileri işleme ve farklı komutları geliştirmek için verilerin kullanılma şeklini düzenleme becerisini ifade eder [2]. Burada veri paylaşımındaki en önemli noktalardan biri, IoT'nin nesneleri geniş ölçekte bağlama (large scale) yeteneğine sahip olmasıdır. ...
Multi-Agent Systems (MAS) make it possible to perceive, collect, share, consolidate and revise information from
multiple smart devices through the design of smart objects as agents within the Internet of Things (IoT) systems.
Although multi-agent systems and related tools significantly change the paradigms used in systems optimization,
the existing literature on MAS is not sufficient to explain modern distributed computing methods describing
enhanced collaboration of IoT devices. This article presents comprehensive research that explains how smart
objects such as sensors, smartphones, and data centers in IoT will affect the system's performance if they are
integrated with MAS technology. In this context, general information about MAS and IoT technologies, the
importance of interoperability in MAS, and how multi-agent technology can be used for various purposes, from
capturing sensor data to decision making, specific to manufacturing systems, are explained. Afterward, technical,
semantic, syntactic, and platform interoperability approaches that will enable communication and interaction of
smart objects in IoT systems and how MAS can contribute to the establishment of these collaborations are
expressed. Finally, it is presented how agent-based interoperability models affect the system's performance with a
centralized and decentralized approach, specific to the manufacturing sector. The research has revealed that multi-
agent systems can be integrated into each layer of the IoT, and in this way, it can increase the effectiveness of IoT
in many areas from information security to efficient use of energy, from routing to increase system efficiency.
... Interestingly, AI located methods commit still undertake over 5G-IoT networks to further develop allure own acting at use, material and network tiers to further reinforce dossier rates by forecasting traffic patterns on the network, accordingly promoting the supply of AI located consumer uses. For example, at the use tier, AI methods maybe took advantage of for learning network traffic and volume flow reasoning to create the network self-configurable, selfarranged and self-adjusting [25]. On material and network coatings, AI located growth algorithms keep ease active range administration, constitute of immense dossier, unification of various instruments, extreme-densification of tools, IoT knots interoperability, and revised artillery history [25]. ...
... For example, at the use tier, AI methods maybe took advantage of for learning network traffic and volume flow reasoning to create the network self-configurable, selfarranged and self-adjusting [25]. On material and network coatings, AI located growth algorithms keep ease active range administration, constitute of immense dossier, unification of various instruments, extreme-densification of tools, IoT knots interoperability, and revised artillery history [25]. Some current and modern AI located uses that maybe backed over 5G-IoT are outlined beneath: ...
The Internet of things is a new revolution that has shifted people's lifestyles from conventional to high-tech. Smart cities, smart homes, pollution management, energy conservation, smart transportation and smart industries are examples of IoT-driven developments. A lot of critical research studies and inspections have existed exhausted order to improve the electronics through IoT. However, there are still plenty of challenges and issues that need to be focused on to reach the full potential of IoT. These challenges and issues must be thought-out from miscellaneous facets of IoT to a degree uses, challenges, permissive sciences, friendly and referring to practices or policies that do not negatively affect the environment impacts etc. The main aim of this review paper is to debate various challenges and key issues of IoT, construction and use of rules. Moreover, this paper shed some light on the existing information and pictorial representations of different facets of IoT. Moreover, the significance of substantial dossier and allure reasoning concerned to IoT has been explored. This paper would help the researchers and analyst to appreciate and allure towards the IoT.
... Additionally, the Internet of Things (IoT) and wearable technology, in conjunction with device-to-device communication (D2D) [20], virtual/augmented reality (VR/AR) [21,22], cyber-physical systems (CPS) [23], artificial intelligence (AI) [24], and smart textiles [25], as well as other developments in 5G communication networks, can enhance human-to-human and human-to-machine connections and interactions. The architecture consists of the following main components: ...
... Additionally, the Internet of Things (IoT) and wearable technology, in conjunction with device-to-device communication (D2D) [20], virtual/augmented reality (VR/AR) [21,22], cyber-physical systems (CPS) [23], artificial intelligence (AI) [24], and smart textiles [25], as well as other developments in 5G communication networks, can enhance human-to-human and human-to-machine connections and interactions. ...
This paper focuses on the use of AI in various MEMS (Micro-Electro-Mechanical System) biosensor types. Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into our daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a number of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. As a result, this paper examines the fundamentals of the neural algorithm and goes into great detail on the fundamentals and uses of the principal component analysis approach. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Our investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors. Focusing on AI and neural networks, this paper introduces Micro-Electro-Mechanical System biosensors using artificial intelligence, which greatly promotes the development of next-generation intelligent sensing systems, and the potential applications and prospects of neural networks in the field of microcantilever biosensors.
... In addition, they focused on establishing plan standards for the improvement of the 5G network [15], optimum resource designation, speed increases for the 5G actual layer brought together, joint enhancement of the start and finish of the actual layer, etc. The resource management solutions for 5G and IoT networks based on machine learning and deep learning have been reviewed in-depth and from top to bottom VOLUME 4, 2016 by [19] and [21]. [3] examined how IoT-produced data is managed for machine learning research and highlighted the existing challenges in helping wise decisions in the IoT environment. ...
Technology’s fast growth has profoundly impacted myriad areas, including healthcare. Implementing 5G networks offering high-speed and low-latency communication capabilities is one of the most promising technical developments. Parallel to this, artificial intelligence (AI) has become a robust data analysis and decision-making tool. This paper examines how 5G and AI are combined in the context of intelligent healthcare systems. T5G green communication systems must overcome several challenges to satisfy the need for more user capacity, faster network speeds, cheaper pricing, and less resource use. By applying 5G standards, data rates, and device dependability for Industry 4.0 applications may be significantly increased. Advanced security and decreased unauthenticated assaults from various platforms are also covered in the paper. An outline of prospective new technologies and security improvements was provided to safeguard 5G-based intelligent healthcare networks. This paper identifies several research issues and potential future directions for secure 5G-based smart healthcare. This article discusses Industry 4.0, 5G standards, and new research in future wireless communications to explore current research concerns related to 5G technology. A brand-new architecture is also suggested in the paper for Industry 4.0 and 5G-enabled intelligent healthcare systems.
... Gu et al. improved the sensing accuracy via dynamical threshold setting [24]. Javaid et al. introduced signal correlation factors into the traditional energy detection threshold [25]. In [26], Shi et al. analyzed the spectrum access systems to ensure their security and privacy against attacks. ...
With the acceleration of economic globalization and integration, the global trade is becoming more frequent, which promotes the vigorous development of transportation industry. In recent years, the Internet of Vehicle (IoV) has developed rapidly in the transportation industry, and the number of IoV users has exploded. The requirements for IoV communication services are very high, resulting in the lack of spectrum resources. Rather than utilizing traditional spectrum resource allocation methods, cognitive radio technology makes full use of idle frequency bands, improving the IoV communication spectrum’s utilization rate. Spectrum sensing is the primary link to realize a cognitive radio. However, IoV mobile communication environment is characterized by complexity, dynamism, and substantial noise interference, thus imposing significant challenges to spectrum sensing. Thus, this paper proposes an intelligent spectrum sensing algorithm based on kernel principal component analysis (KPCA) and an improved convolutional neural network (CNN). Since the wireless signal cannot distinguish the signal and noise linearly, KPCA maps the sampled signal to a high-dimensional space, creates a covariance matrix, and obtains eigenvector data of the signal and noise through matrix decomposition. A spectrum sensing classifier based on improved CNN is proposed, and the dynamic threshold is obtained via offline training. Compared with the traditional algorithm, the designed deep CNN improves the model’s training speed, enables parameter sharing, and reduces the number of model parameters, effectively reducing the computational complexity. Additionally, due to the extracted signal feature’s small dimension, the algorithm reduces the number of pooling layers and avoids the effective features’ loss, thus increasing the detection probability. Finally, the proposed algorithm achieves a 10% higher sensing accuracy than support vector machine (SVM), Elman, and LeNet5 algorithms, signaling its robustness.
... AI-based methods are capable of extracting patterns from the data, making meaningful interpretations of it and recommending actions to the end devices. While discussing the existing challenges and necessary solutions based on IoT and 5G enabling technologies, Javaid et al. [34] focused on the demands for AI in future IoT-based 5G network systems. The integration of AI at the fog nodes near the end devices was discussed in order to minimize energy dissipation, optimize communication latency, improve link capacity, and enhance the Table 2 Challenges, benefits and potential solutions for IIoT. ...
IIoT-enabled technologies and infrastructure, their role in global industrial growth, applications, challenges, and future directions. IIoT applications use the intelligence of things to solve industrial problems like supply chain mismanagement, data privacy risks, a weak cloud strategy, cost containment, and others. For instance, fog computing reduces parking, platform, fuel, and CO2 emissions. A blockchain-based security framework for the cement sector can resolve 51% of security issues and Sybil attacks caused by consensus algorithms like Proof of Work (PoW). Major companies' performance depends on well-designed IIoT infrastructure, despite significant challenges. Industrial technologies will improve as research and experimentation advance IIoT infrastructure.
... Various options and frames for protecting the Network edge layer were developed to deal with risk occurrence. By a heuristic technique, most offered designs can only solve certain safety problems between peripheral results in improved and one IoT framework functioning layer [19]. Even though the existing systems manage data security, the system's sustainability must be considered, which is a major problem. ...
Security issues and Internet of Things (IoT) risks in several areas are growing steadily with the increased usage of IoT. The systems have developed weaknesses in computer and memory constraints in most IoT operating systems. IoT devices typically cannot operate complicated defense measures because of their poor processing capabilities. A shortage of IoT ecosystems is the most critical impediment to developing a secured IoT device. In addition, security issues create several problems, such as data access control, attacks, vulnerabilities, and privacy protection issues. These security issues lead to affect the originality of the data that cause to affects the data analysis. This research proposes an AI-based security method for the IoT environment (AI-SM-IoT) system to overcome security problems in IoT. This design was based on the edge of the network of AI-enabled security components for IoT emergency preparedness. The modules presented detect, identify and continue to identify the phase of an assault life span based on the concept of the cyberspace killing chain. It outlines each long-term security in the proposed framework and proves its effectiveness in practical applications across diverse threats. In addition, each risk in the borders layer is dealt with by integrating artificial intelligence (AI) safety modules into a separate layer of AI-SM-IoT delivered by services. It contrasted the system framework with the previous designs. It described the architectural freedom from the base areas of the project and its relatively low latency, which provides safety as a service rather than an embedded network edge on the internet-of-things design. It assessed the proposed design based on the administration score of the IoT platform, throughput, security, and working time
... The existing technologies also require more and better functionalities, lower transmitting power, and spectrum sharing to maximize the network capacity. A new spectrum-efficient (SE) data modulation technique is reported to meet the requirements of advanced high-density IoT networks [4]. ...
Spectrum-efficient, high-density, and high-speed data transmission are essential to store and exchange sensitive information through Internet of Things (IoT) networks. However, the resource-constrained IoT devices and the limited existing frequency spectrum pose a significant challenge to employing the more efficient technique for the next-generation technology. This article presents an innovative pulse index modulation (PIM) architecture with a randomization technique for analog pulse-based packet-less high-volume data transmission. The pulse-based compression simplifies the encoding and decoding schemes for short-range wireless telemetry. The pulse randomization technique creates the pulse blinding by reordering the pulse positions and adds an extra level of physical-layer security. This article describes the design, simulation, and prototype development of PIM to validate the feasibility and compatibility of pulse-based data telemetry using the standard architecture. Simulation results show that the proposed PIM increases the data compression ratio by 2.61 times and improves the processing time by 5.56 time compared to the Huffman coding for a 3-bit system. Test results show that the BER is
$\sim 7.5\,\,\times \,\,10^{-4}$
at 10.0 dB SNR, which satisfies the lower bound for data communication and increases the transmission speed
$k$
-times by supporting
${2^{k}*k}$
bits data using
${2^{k}}$
number of pulses, where
$k$
is a nonnegative integer number. The proposed PIM has the potential to improve data rate with added security to support the next-generation IoT networks.
... In the near future, apparel and wearable technology may be used more widely. To provide them great capabilities, the clothing and wearables would connect with other clothing and wearables, as well as with external items and internet servers [19]. The Internet of Smart Clothing is a concept that is built on the foundation of this domain. ...
Textiles are a sophisticated and ancient technology with many appealing qualities. They are frequently soft and are readily folded, twisted, sliced, or deformed. When under tension, textiles can hold their shape and can even be manufactured to have different degrees of stretchability. Smart wearables and IoT-based clothing have the potential to have a significant impact by balancing functionality and the joy that fashion brings, along with the rise of the Internet of Things (IoT). It is now possible to easily fabricate both soft materials with embedded flexibility and stiff objects with embedded flexibility by combining textiles and 3D printing. In order to reinvent technology that can anticipate wants and desires, smart clothing tries to strike a balance between engineering, cybersecurity, interface, fashion, user experience, design, and science. The increasing merging of textiles and electronics now allows for the seamless and widespread integration of sensors into textiles, and conductive yarns have been developed to make this possible.
... A.I. helps by processing massive raw data generated by a huge number of smart devices at the edge to reduce data size, giving insights, and making efficient decisions out of it. These applications rely on 5G's fast bandwidth [12,13,14]. In the 5G context, AI can directly benefit the driving technologies such as SDN and NFV to be integrated into MEC and IoT. ...
Integration of IoT and 5G enables us to fulfil today’s need to create smart residential buildings to enhance life quality and safety in various aspects. This paper proposes the design and implementation of a 5G IoT based Smart Residential Building using the most recent version of CISCO Packet Tracer (a simulation software). Different smart IoE devices were used for automation which allow distant monitoring and controlling. Since these buildings are vulnerable to cyber-attacks and security threats, this paper also analyzes the proposed security framework and how such an implementation on using various sensors and actuators enables us to enhance the security and safety. In addition to this, we also outline the measures to be taken by the government and building owners to strengthen the security. The simulation results show that integrating 5G and IoT is a promising and cost-effective if it gets implemented practically in the real world.
... In summary, efficiency, security and privacy are very elusive issues in 5G networks as none of the schemes above effectively addresses this trio. Efficient handovers assures higher data rates and effective utilization of the network resources [39]. In addition, there is need for an authentication protocol that has very little communication and computation costs so as to be energy efficient in terms of power consumptions [40]. ...
The fifth generation (5G) networks have been deployed in some countries to offer high data rate connectivity, ultra-low latencies and increased capacities. However, security, efficiency and privacy are major issues affecting these deployments. Although a myriad of intelligent target cell section protocols has been developed, their main focus is on efficiency and quality of service improvements. As such, security and privacy are missing in these protocols. To address this gap, the third generation partnership group (3GPP) has specified authentication and key agreement (5G-AKA), and extensible authentication protocol–improved AKA (EAP-AKA’) in its Release 16(3GPP R16). However, these two protocols are susceptible to numerous attacks. To curb some of these security issues, many protocols have been presented in literature. However, these schemes are inefficient or fail to effectively meet 5G security and privacy requirements. In this paper, a protocol that simultaneously addresses efficiency, security and privacy is developed. To achieve this, an intelligent model leveraging on artificial neural network and fuzzy logic is trained and deployed for target cell prediction. During the actual handover, the user equipment, source gNB and target gNB are authenticated and a session key established. The results show that this protocol has high handover success rate and average computation and communication overheads. It offers anonymity, forward key secrecy, untraceability and is robust against numerous attack vectors.
... Gu et al. improved the sensing accuracy via dynamical threshold setting [24]. Javaid et al. introduced signal correlation factors into the traditional energy detection threshold [25]. In [26], Shi et al. analyzed the spectrum access systems to ensure their security and privacy against attacks. ...
With the acceleration of economic globalization and integration, the global trade is becoming more frequent, which promotes the vigorous development of transportation industry. In recent years, the Internet of Vehicle (IoV) has developed rapidly in the transportation industry, and the number of IoV users has exploded. The requirements for IoV communication services are very high, resulting in the lack of spectrum resources. Rather than utilizing traditional spectrum resource allocation methods, cognitive radio technology makes full use of idle frequency bands, improving the IoV communication spectrum’s utilization rate. Spectrum sensing is the primary link to realize a cognitive radio. However, IoV mobile communication environment is characterized by complexity, dynamism, and substantial noise interference, thus imposing significant challenges to spectrum sensing. Thus, this paper proposes an intelligent spectrum sensing algorithm based on kernel principal component analysis (KPCA) and an improved convolutional neural network (CNN). Since the wireless signal cannot distinguish the signal and noise linearly, KPCA maps the sampled signal to a high-dimensional space, creates a covariance matrix, and obtains eigenvector data of the signal and noise through matrix decomposition. A spectrum sensing classifier based on improved CNN is proposed, and the dynamic threshold is obtained via offline training. Compared with the traditional algorithm, the designed deep CNN improves the model’s training speed, enables parameter sharing, and reduces the number of model parameters, effectively reducing the computational complexity. Additionally, due to the extracted signal feature’s small dimension, the algorithm reduces the number of pooling layers and avoids the effective features’ loss, thus increasing the detection probability. Finally, the proposed algorithm achieves a 10% higher sensing accuracy than support vector machine (SVM), Elman, and LeNet5 algorithms, signaling its robustness.
... There are many researchers recognized the power of 5G. For example, an illustration of 5G digital continuum from sensing and computing perspective is presented in [2], Opportunities and challenges for Internet of Thing (IoT)-based 5G network are summarized in [3]. A remote control application introduced in [4] shows the effectiveness of combining 5G and image processing at the edge by use of GPU. ...
5G wireless technology can deliver higher data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more uniform user experience to users. It brings additional power to help address the challenges brought by renewable integration and decarbonization. In this paper, a 5G enabled adaptive computing workflow has been presented that consists of various computing resources, such as 5G equipment, edge computing, cluster, Graphics processing unit (GPU) and cloud computing, with two examples showing technical feasibility for edge-grid-cloud interaction for power system real-time monitoring, security assessment, and forecasting. Benefiting from the high speed data transport and massive connection capability of 5G, the workflow shows its potential to seamlessly integrate various applications at distributed and/or centralized locations to build more complex and powerful functions, with better flexibility.
... N. Nomikos environments, while the fourth and fifth generations (4G and 5G) of mobile communications have put special emphasis in the coexistence of mobile users and Internet-of-Things (IoT) devices [1]- [4]. Unfortunately, most network architectures and communication techniques were designed for land-based communications, while the maritime domain has been largely neglected from this revolution. ...
Maritime activities represent a major domain of economic growth with several emerging maritime Internet of Things use cases, such as smart ports, autonomous navigation, and ocean monitoring systems. The major enabler for this exciting ecosystem is the provision of broadband, low-delay, and reliable wireless coverage to the ever-increasing number of vessels, buoys, platforms, sensors, and actuators. Towards this end, the integration of unmanned aerial vehicles (UAVs) in maritime communications introduces an aerial dimension to wireless connectivity going above and beyond current deployments, which are mainly relying on shore-based base stations with limited coverage and satellite links with high latency. Considering the potential of UAV-aided wireless communications, this survey presents the state-of-the-art in UAV-aided maritime communications, which, in general, are based on both conventional optimization and machine-learning-aided approaches. More specifically, relevant UAV-based network architectures are discussed together with the role of their building blocks. Then, physical-layer, resource management, and cloud/edge computing and caching UAV-aided solutions in maritime environments are discussed and grouped based on their performance targets. Moreover, as UAVs are characterized by flexible deployment with high re-positioning capabilities, studies on UAV trajectory optimization for maritime applications are thoroughly discussed. In addition, aiming at shedding light on the current status of real-world deployments, experimental studies on UAV-aided maritime communications are presented and implementation details are given. Finally, several important open issues in the area of UAV-aided maritime communications are given, related to the integration of sixth generation (6G) advancements.
... Thus, more 5G antennas permit for precise location tracking of users inside and outside. Further, International Mobile Subscriber Identity (IMSI) is prone to reveal identity of mobile users [23]. In this regard, mobile network carriers and network consortium should take responsibility to provide users with digital safety and protect their confidential data with the implementation of cutting-edge security solutions. ...
... e undergraduate students must participate in regular physical activity as quickly as possible in the center [19]. e school teaching days, student medical guidelines, and policies of education account for 7.9%, primary schools, high schools, and only 2.1% of 3.8% [20]. e prize PEP-appropriate central and high school understudies have a variety of functions. ...
With the continuous growth of science and technology, mankind has entered the fifth-generation (5G) era. In this background, the development of many fields will face great opportunities and challenges, including the field of physical education (PE). The traditional teaching mode, method, and contents of PE are difficult to adapt to the development needs of the 5G era. Therefore, it is of great significance to study the PE teaching reform in the era of “5G education.” Moreover, integrating 5G technology and PE may benefit students, educators, and the entire PE system. This study offers an in-depth investigation of the reforms and development of PE services under the background 5G interconnected communications. The reforms of PE and services are examined using the most up-to-date 5G technologies. Four 5G methodologies which include model-based practice (MBP), virtual reality (VR), the Internet of Things (IoT), and artificial intelligence (AI) are analyzed, and for the comparative study, performance indicators such as cost reduction, energy efficiency, and security level are measured. When compared to other strategies, IoT-based physical education is found to be more efficient in terms of these parameters. The 5G-driven PE will provide students with objective, fair, and diversified education, and adaptive learning services to promote the overall development of students.
... Combined with the Internet and wireless network transmission technology, a reliable data transmission network can be formed to realize real-time and accurate collection and transmission of object information and to achieve the ubiquitous connection between information objects. Intelligent process processing can use AI technology to make production processes more intelligent, which is still based on the transmission and analysis of sensory data and information [11]. Based on the IoT characteristics and combined with the information science perspective, intelligent processes around information flow can be constructed, the IoT information processing process can be summarized as shown in Figure 1, including original data collection, data filtering, data storage, and data analysis. ...
The Internet of Things (IoT) wireless network technology is gradually making its way into campus life in today’s information-driven modern world, bringing convenience to students’ daily lives and studies while also placing new demands on the quality of teaching and management effectiveness of universities. In order to make colleges and universities have a more rational approach to talent training, relevant workers need to grasp the characteristics of the data era, keep up with excellent educational examples, innovate educational and teaching methods, and guide students’ learning and growth in the data era. To that end, this paper begins by examining the practicality and importance of IoT for teaching and management in colleges and universities by examining the current state of teaching in colleges and universities, the application of IoT in colleges and universities, and the shortcomings of IoT, as well as the use of network technology on campus. Furthermore, it proposes the IoT education management platform combined with machine learning technology. Finally, we offer an IoT education management platform that combines machine learning technologies, which we believe will be useful to relevant practitioners.
... In summary, efficiency, security and privacy are very elusive issues in 5G networks as none of the schemes above effectively addresses this trio. Efficient handovers assures higher data rates and effective utilization of the network resources [ 39 ]. In addition, there is need for an authentication protocol that has very little communication and computation costs so as to be energy efficient in terms of power consumptions [ 40 ]. ...
Base station ultra-densification in 5G networks offer high bandwidths, data rates and extremely low delay budgets in line with the ITU specifications. However, high mobility among subscribers imply frequent crossing of cell boundaries. For increased security protection, these handoffs must be authenticated. Although many AKA protocols have been designed for this purpose, poor performance and many vulnerabilities are inherent in these protocols. It is therefore possible for these vulnerabilities to be exploited to launch attacks against the core network or the interconnected devices. In this paper, a review of the conventional AKA protocols is provided, followed by the development of an enhanced AKA protocol. Formal security analysis using AVISPA and ProVerif demonstrates its robustness against attacks as well as the secrecy of the derived keys. In addition, its data and control plane delay budgets are shown to be within the ITU specifications.
... In Wireless Sensor Internet of Things (WSIoTs) [1], [2], the Ordinary Sensor Nodes (OSNs) are deployed in the environment for its monitoring. The OSNs send data to main servers, which are responsible to aggregate the data sensed by ONS. ...
In the above article
[1]
, reference
[2]
is updated and the missing DOI is provided. In Section IV “Proposed System Model” of the article, a two-point distance formula is added which is taken from
[3]
. The text is updated as follows: “In order to send the sensed data, the OSN follows the shortest path. The OSN finds the shortest distance between itself and nearby SN using the x and y coordinates. As we have deployed a two-dimensional (2D) network. So, the above-mentioned distance is being calculated with the help of the two-point distance formula:
... Due to the spectrum scarcity issue, establishing connections among these many devices is challenging at 5G mid-bands. Cognitive radio (CR) enabled 5G -mMTC technology is a prominent solution to resolve this problem Javaid et al. [6];Ahmad et al. [2]. Spectrum sensing (SS) is a significant function in the CR life cycle to identify unused spectrum bands in radio frequency (RF) environments. ...
Massive machine-type communications (mMTC) face spectrum scarcity problems at 5G mid-bands (i.e., sub 6 GHz) due to tens of billions of machine-type devices connected in a smaller region. The mMTC facing significant challenges are scalability and efficient connectivity. To enable cognitive radio (CR) in 5G mMTC technology to resolve issues and gives promising solutions. Dynamic spectrum assignment (DSA) is mainly used to solve spectrum scarcity issues that provide efficient connectivity to massive devices. Spectrum sensing (SS) is an integral part of the CR used to detect spectrum opportunities in the spectrum. Energy detection (ED) is a prominent sensing mechanism, and a threshold computation is essential to find accurate spectrum opportunities in the spectrum. The massive devices in mMTC communication send small messages and face short-term fluctuations during sensing at the sub 6 GHz bands. Hence, threshold calculation is a critical challenge in SS at sub 6 GHz bands that depend on two key factors: signal and noise variance. At 5G mid bands, the high random nature of the signal input gives poor accuracy to find spectrum holes under the assumption that the channel is either static or quasi-static in a non-line-of-sight (NLOS) scenario. Thus, a novel spectrum sensing with an efficient threshold over η-μ fading channel is proposed. The key implementation is the moving average energy (MAE) mechanism to minimize short-term fluctuations in signal energy computation and delay variance that reduces sensing delay under fading conditions. The noise variance is measured from the upper bound limit of the noise interval. The SS mechanism implemented on the real-time testbed and GNU radio processing blocks on 3.3–3.8 GHz frequency bands using universal software radio peripheral (USRP)-2953 RIO. The experimental outcomes show a high probability detection rate and low sensing delay at 5G mid-bands.
... The adoption of a risk-based approach to ethical assessment can be greatly simplified by the adoption of a methodology or framework which will drive the researcher in such a process. The framework presented in this paper represents a first step in such a direction [1,7,12,15,19]. ...
In the last few years many scholars, public and private organizations have been involved in the definition of guidelines and frameworks for individuating the principles to adopt in the development and deployment of AI systems. Some authors, however, noted that the effectiveness of these guidelines or ethical codes on the developer’s community is very marginal. One of the obstacles that opposes to the effective implementation of ethical principles is the lack of an approach for solving tensions which arise when principles are applied. A possible solution to such an issue could be the adoption of a risk-based approach which is also advocated by many sources. To our knowledge, no concrete proposals have been presented in literature on how to perform a risk-based ethical assessment. In this paper we contribute to close this gap by introducing a framework based on a qualitative risk analysis approach for assessing the ethical impact underneath the introduction of an innovation either technological or organizational in a system. We will also show how the framework can be used for individuating suitable safeguards to adopt for balancing potential ethical infringements that the innovation may entail once implemented. Some case studies in the cybersecurity context are also described for showing the effectiveness of our approach.
... Wireless Sensor Networks (WSNs) have a significant impact on increasing the capabilities of the Internet of Things (IoT) [1,2]. In WSNs, network devices are widely used for many practical applications, such as health [3], transportation [4][5][6], agriculture [7,8], and education [9]. However, the failure of these network devices causes a great loss in an entire network system. ...
The enhancement of Robustness (R) has gained significant importance in Scale-Free Networks (SFNs) over the past few years. SFNs are resilient to Random Attacks (RAs). However, these networks are prone to Malicious Attacks (MAs). This study aims to construct a robust network against MAs. An Intelligent Rewiring (INTR) mechanism is proposed to optimize the network R against MAs. In this mechanism, edge rewiring is performed between the high and low degree nodes to make a robust network. The Closeness Centrality (CC) measure is utilized to determine the central nodes in the network. Based on the measure, MAs are performed on nodes to damage the network. Therefore, the connections of the neighboring nodes in the network are greatly affected by removing the central nodes. To analyze the network connectivity against the removal of nodes, the performance of CC is found to be more efficient in terms of computational time as compared to Betweenness Centrality (BC) and Eigenvector Centrality (EC). In addition, the Recalculated High Degree based Link Attacks (RHDLA) and the High Degree based Link Attacks (HDLA) are performed to affect the network connectivity. Using the local information of SFN, these attacks damage the vital portion of the network. The INTR outperforms Simulated Annealing (SA) and ROSE in terms of R by 17.8% and 10.7%, respectively. During the rewiring mechanism, the distribution of nodes’ degrees remains constant.
... The intricacies of wired detection lines restrict the flexibility of wired monitoring. The maintenance and management costs are also high [8,9]. Here, an artificial intelligence (AI) monitoring warehouse storage system is built using ZigBee wireless network technology. ...
The study expects to reduce the development cost and energy consumption of the storage environment monitoring and improve the efficiency of the storage monitoring environment. Firstly, the storage environment monitoring system is designed in detail using ZigBee. It includes the design of terminal nodes, router nodes, coordinator nodes, and upper computer software. Here is a detailed description of the process of establishing a communication network for three different types of devices in the ZigBee network. The address allocation mechanism of the ZigBee network is introduced. Then, through the application of activity-based costing, the cost reduction is achieved as expected. Finally, the evaluation model of the storage logistics cost level is established, and the various reasons that affect the storage logistics cost are analyzed. The completed warehouse environment monitoring system is a tree topology network composed of a ZigBee coordinator, several ZigBee routing nodes, and terminal devices through the above design. The coordinator in the network is responsible for establishing the network, and it can communicate with the host computer through the serial port. The terminal node collects environmental parameter information and feeds the data back to the ZigBee coordinator through wireless multihop. The ZigBee routing node is mainly used to expand the range of the network to achieve the purpose of wireless monitoring of the entire storage environment. This provides a reference for the combination of wireless communication technology and sensor technology.
... When compared to existing methodologies for intelligence applications used in areas such as business analytics, the usage of ML simply makes such prediction or analytical operations perform much more efficiently than ever before. Other AI technologies such as Speech Recognition, CV, and DL also helps in drawing insights from the data that required human intervention in former time [4]. Basically, it can be concluded that the application of AI in IoT simply enables us to attain multiple goals such as resolving issues with unexpected outages, achieve more efficiency, develop novel and improved applications and enhance the project management as well. ...
“Internet of Things” is on the path of revolutionizing traditional technologies in multiple facets. The trend of the future is expected to be Artificial Intelligence enabled IoT (AIoT) due to the widespread applicability of the technology. The compactness of IoT devices leveraged with the powerful nature of AI makes it an ideal alternative for the cumbersome systems currently in use. The increasing population and the need for advancements are facilitating the growth of the technology even faster. The application domains of AIoT are vast and vivid. From healthcare to autonomous transports, robotics to smart cities, everywhere the traces are visible. With all this being said, a keen interest should be given to the sustainable aspect of technological development as well. With the resources ever-shrinking and the population increasing, sustainability is the need of the era. The high efficiency and power-saving nature of IoT devices along with their high versatility in work makes it a paragon choice for sustainable technologies. Through this work, we provide an overview of intelligent IoT from multiple angles. The need, as well as the methods of implementing AIoT, is also presented. We also discuss the multiple application domains making use of this technology.
A large number of sensors are deployed for performing various tasks in the smart cities. The sensors are connected with each other through the Internet that leads to the emergence of Internet of Things (IoT). As the time passes, the number of deployed sensors is exponentially increasing. Not only this, the enhancement of sensors has also laid the base of automation. However, the increased number of sensors make the IoT networks more complex and scaled. Due to the increasing size and complexity, IoT networks of scale-free nature are found highly prone to attacks. In order to maintain the functionality of crucial applications, it is mandatory to increase the robustness of IoT networks. Additionally, it has been found that scale-free networks are resistant to random attacks. However, they are highly vulnerable to intentional, malicious, deliberate, targeted and cyber attacks where nodes are destroyed based on preference. Moreover, sensors of IoT network have limited communication, processing and energy resources. Hence, they cannot bear the load of computationally extensive robustness algorithms. A communication model is proposed in this paper to save the sensors from computational overhead of robustness algorithms by migrating the computational load to back-end high power processing clusters. Elephant Herding Robustness Evolution (EHRE) algorithm is proposed based on an enhanced communication model. In the proposed work, 6 phases of operations are used: initialization, sorting, clan updating, clan separating,selection and formation, and filtration. These process collectively increase the robustness of the scale-free IoT networks. EHRE is compared with well-known previous algorithms and is proven to be robust with a remarkable lead in performance. Moreover, EHRE is capable to achieve global optimum results in less number of iterations. EHRE achieves 95% efficiency after 60 iterations and 99% efficiency after 70 iterations. Moreover, EHRE performs 58.77% better than Enhanced Differential Evolution (EDE) algorithm, 65.22% better than Genetic Algorithm (GA), 86.35% better than Simulating Annealing (SA) and 94.77% better than Hill climbing Algorithm (HA).
In heterogeneous Internet of Things (IoT) networks, various communication technologies lead to different transmission ranges of nodes, and they can cooperatively provide seamless communication. Unfortunately, the flexible communication mode offers more chances for malware to invade the IoT devices. To maintain its cyber security, two key issues, i.e. the critical threshold of the onset of malware propagation and the lowest-cost defense strategy after it occurs, need to be addressed. To solve the first challenge, we construct a dynamics model by using the degree-based mean-field theory and point process theory, to study the malware propagation-defense process among heterogeneous IoT devices. We analytically derive the closed-form expression of the critical malware transmission rate which can be used to predict whether the malware can propagate or not. For the latter problem, we investigate the equivalent conditions of degree-related patching strategies in defense effectiveness, which can be used to determine the lowest-cost one more directly. In addition, We compare different transmission ways of malware, and find that the malware infection is hard to avoid under the way of centralized transmission, but the decentralized transmission has a greater risk of large-scale infection. We also explore how the immunization measures and the different communication frequencies affect malware propagation. The results show that it is significant to identify important devices for immunization and infected cluster may form in some cases. Our results offer a theoretical foundation to predict and defense malware propagation in heterogeneous IoT networks.
A thin, flexible, and transparent polyethylene terephthalate (PET) based screen-printed band-stop frequency selective surface (FSS) with ink minimization is experimentally demonstrated at 28 GHz using both planar and conformal configurations. A miniaturized conventional FSS unit cell is ink-minimized using surface meshing without compromising the angular stability of the transmission response of the surface within ±60°. This not only leads to reduced amount of expensive ink required in prototyping, thereby lowering the overall manufacturing cost, but also increases the optical transparency of the structure by a factor of 65% using an 80
$\mu \text{m}$
linewidth tolerance. Finally, the operation of the ink-minimized FSS is experimentally shown using a conformal geometry with two radii of curvature (60 and 114 mm) and a good filtering performance is confirmed. Useful for 5G electromagnetic interference (EMI) applications, these FSSs feature increased feasibility through improved transparency and reduced cost due to ink minimization.
Thanks to the express rise of digitalization, Artificial Intelligence, and Android Communication Technologies, the internet has gradually encroached into many aspects of our daily lives dependent on the maintenance of the status quo. In the era of digital technology, it has grown into a significant field that is closely related to the future of the nation. For instance, the Internet has permeated every classroom, every dorm, and every college student's daily study routine. College students have emerged as the Internet's most aggressive adopters of new technologies. This will help more swiftly identify the effects of teaching and learning. Roles and permissions for users can also be managed by it. This kind of integrated "network online course" is one that colleges and universities are implementing more frequently. The range, timeliness, interaction, and breadth of the computer network can enhance traditional education and provide ideological and intellectual education in colleges and universities a new lease on life. Classroom management and lesson plans go hand in hand for any improved and effective learning. However, the proliferation of the IoT and the 5G network had a significant negative influence on this improvement in many ways. This paper examined the Impacts of Internet of Things (Iot) and 5G Network on Technology Enhanced Learning (Tel) and make reccomendations to mitigate problematic impacts
Since Internet Protocol version 6 is a new technology, insecure network configurations are inevitable. The researchers contributed a lot to spreading knowledge about IPv6 vulnerabilities and how to address them over the past two decades. In this study, a systematic literature review is conducted to analyze research progress in IPv6 security field following the Preferred Reporting Items for the Systematics Review and Meta-Analysis (PRISMA) method. A total of 427 studies have been reviewed from two databases, IEEE and Scopus. To fulfil the review goal, several key data elements were extracted from each study and two kinds of analysis were administered: descriptive analysis and literature classification. The results show positive signs of the research contributions in the field, and generally, they could be considered as a reference to explore the research of in the past two decades in IPv6 security field and to draw the future directions. For example, the percentage of publishing increased from 147 per decade from 2000-2010 to 330 per decade from 2011 to 2020 which means that the percentage increase was 124%. The number of citations is another key finding that reflects the great global interest in research devoted to IPv6 security issues, as it was 409 citations in the decade from 2000-2010, then increased to 1643 citations during the decade from 2011 to 2020, that is, the percentage increase was 302%.
Maritime activities represent a major domain of economic growth with several emerging maritime Internet of Things use cases, such as smart ports, autonomous navigation, and ocean monitoring systems. The major enabler for this exciting ecosystem is the provision of broadband, low-delay, and reliable wireless coverage to the ever-increasing number of vessels, buoys, platforms, sensors, and actuators. Towards this end, the integration of unmanned aerial vehicles (UAVs) in maritime communications introduces an aerial dimension to wireless connectivity going above and beyond current deployments, which are mainly relying on shore-based base stations with limited coverage and satellite links with high latency. Considering the potential of UAV-aided wireless communications, this survey presents the state-of-the-art in UAV-aided maritime communications, which, in general, are based on both conventional optimization and machine-learning-aided approaches. More specifically, relevant UAV-based network architectures are discussed together with the role of their building blocks. Then, physical-layer, resource management, and cloud/edge computing and caching UAV-aided solutions in maritime environments are discussed and grouped based on their performance targets. Moreover, as UAVs are characterized by flexible deployment with high re-positioning capabilities, studies on UAV trajectory optimization for maritime applications are thoroughly discussed. In addition, aiming at shedding light on the current status of real-world deployments, experimental studies on UAV-aided maritime communications are presented and implementation details are given. Finally, several important open issues in the area of UAV-aided maritime communications are given, related to the integration of sixth generation (6G) advancements. These future challenges include physical-layer aspects, non-orthogonal multiple access schemes, radical learning paradigms for swarms of UAVs and unmanned surface and underwater vehicles, as well as UAV-aided edge computing and caching.
Smart Textiles Are Intelligent Textile Structure That Can Sense And React To Environmental Stimuli, Which May Be Mechanical, Thermal, Chemical, Biological, And Magnetic Among Others. Research And Development Towards Wearable Textile-Based Personal Systems Allowing E.G. Health Monitoring, Protection & Safety, And Healthy Lifestyle Gained Strong Interest During The Last 10 Years. The Functionalities Include Aesthetic Appeal, Comfort, Textile Soft Display, Smart Controlled Fabric, Fantasy Design With Color Changing, Wound Monitoring, Smart Wetting Properties And Protection Against Extreme Variations In Environmental Conditions. This Paper Describes About Smart Textiles And Some Types Of Smart Textiles Used In Industry. It Also Describes The Current Status Of Research And Development Of Wearable Systems By Reporting The Salient Characteristics Of The Most Promising Projects Being Developed And The Future Challenges In This Area.
Mobile edge computing and nonorthogonal multiple access (NOMA) have been considered as promising technologies that can satisfy rigorous requirements of industrial Internet of Things systems. However, system dynamics, including channel states and computation task requests, may continuously change NOMA decoding order and computation uploading time, making it difficult to reduce latency using conventional highly complex optimization methods. In this article, we investigate a novel scheme that effectively reduces the average task delay to improve the quality of service for all users by jointly optimizing subchannel assignment (SA), offloading decision (OD), and computation resource allocation (CRA). To deal with the high complexity, the original multiserver problem is first decomposed into multiple single-server problems. Subsequently, each single-server problem is decoupled into CRA and SA/OD subproblems. Using convex optimization, a closed-form solution is derived for the optimal CRA action. Concurrently, the optimal SA/OD action is obtained using a distributed multiagent deep reinforcement learning algorithm. Simulation results reveal that the proposed scheme significantly outperforms the state-of-the-art schemes. In particular, it reduces the action decision duration by 30 times while achieving a near-optimal performance of up to 97% of the optimum under the exhaustive search scheme.
This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program.
5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G- enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co- simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders.
In summary, our main technical highlights in project Year 1 are as follows:
1) Technical characterization of 5G standalone architectures
2) Formulation of co-simulation test case of T&D&C networks embedded with 5G
3) Initial benefit evaluation of 5G communication platform for grid use cases
4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions.
In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications
This study presents an ambient intelligence oriented, topological robustness scheme for internet of things (IoT). The scheme primarily exploits the underlying geometric properties of scale-free IoT networks for a substantial improvement of genetic algorithm (GA) based state of the art robustness techniques. The geometrically optimized GA (Go-GA) is subsequently extended to traditional heuristics algorithms by proposing their geometrically optimized variants. All three techniques are comparatively evaluated over a simulated scale-free IoT architecture employing Schneider R as metric of robustness. The study follows a data-driven approach where information about nodes and edges is pulled from a central big data server, and topological robustness of a given scale-free IoT is tested against existing benchmarks. The proposed scheme aims to achieve convergence to global optima and conserve computational costs by efficient edge swapping (EES) and node removal based thresholding (NRT). Performance evaluations show that Go-GA outperforms state of the art variants of GA by a margin of 20% for Schneider R. Traditional techniques of hill climbing algorithm (HCA), simulated annealing algorithm (SAA) and ROSE also improve by a margin of 11%, 12% and 14% respectively with consideration of geometric aspects. Moreover, as the network size increases, a mere decline of 7.6% in robustness R is observed for Go-GA as compared to 18% degradation for classical algorithms.
In Albania is difficult to discuss about the research in the field of innovation because often the efforts invested in this aspect have been experimental and do not go deep into the problem. The purpose of this paper is to find a description and reference of the history of innovation, its definition, combination of various dimensions in the literature as well as its determinants studied up to today. The study in this aspect tries to have theoretical depth, producing new and systematized knowledge based on careful literature review, it aims at a systematic literature review in order to consolidate the concept of innovation in a less developed field and without a strong research base in the Albania. An alternative way to set in motion economies that are experiencing a slowdown in their growth, it is the innovation, which it has been treated as the new industrial revolution (Kumar and Sundarraj, 2016). Of course, it highlight the new paradigm according to which the engagement of new technologies and the use of existing technologies in different ways, enable the creation of a new economy and new opportunities for further developments. According to Taalbi (2017), it is confirmed a positive relationship between innovation and performance, so innovative firms actually have better performance. According to the recent data of June 2022 from the Word Bank, Albania is the last in the region with 0.15% of GDP for the research and development expenditure. Albania not only has the lowest level in terms of research and development but also has a deep difference with both European and regional countries.
The growing volume of research and the development of new backend platforms for the Internet of Things (IoT) reinforce the proposition of new architectures that offer greater flexibility, a high degree of integration and greater capacity for managing and processing context information. Especially in the face of a new horizon paved by disruptive technologies such as Software- Defined Networking (SDN) and Management and Network Orchestration (MANO) present in 5G networks. Fog computing occupies a prominent place in this scenario, as it extends computing capabilities to the levels located between IoT devices and the cloud, corroborating the establishment of a broader scope, the CloudtoThings Continuum. However, the success of the CloudtoThings Continuum requires a new generation of IoT platforms capable of embracing this new paradigm to allow the management and processing of context information to be performed at multiple levels of the network. Given this scenario, this doctoral thesis proposes the Helix Multi-layered platform, inspired by FIWARE, which presents an architecture based on the horizontal and vertical federation of brokers endowed with advanced resources to enable the management and processing of context information to be distributed at multiple levels of the network. The Helix Multi-layered platform establishes a Cloud-to-Things Continuum from the integration of new virtualized infrastructure technologies, acting as a middleware that offers a holistic view between context producers and consumers located at the cloud, fog and edge levels of this continuous. Furthermore, it provides operating modes mediated by Helix Brokers distributed in the Cloud-to-Things Continuum, which, depending on the application architecture, allow expanding the processing capacity, merging, and dissemination of context information through the available infrastructure, in addition to enabling device-to-device communication across edge-to-edge, edge-to-cloud, fog-to-cloud and cloud-to-cloud flows. Cloud Context Information Management (CCIM) and Helix Brokers use standardized data models, enable the use of entity relationships, conditional subscriptions, geolocation operations, and can be associated with IoT agents capable of interoperating with IoT protocols. The modules and components of the platform were evaluated through laboratory experiments and Proof of Concepts (PoCs), highlighting the real-world testbed conducted in an industrial environment and at the Aveiro Tech City Living Lab. In addition, the platform was evaluated in a testbed compatible with the 5G vision of the European Telecommunications Standards Institute (ETSI), on a scenario that is based on the Novel Enablers for Cloud Slicing (NECOS) platform for automating the instantiation of the Helix Broker in cloud-network slices. The experiments allowed us to evaluate and validate the modules, components, and operating modes of the Helix Multi-layered platform in different use cases. The results obtained suggest that the operating modes provided by Helix Multi-layered allowed a reduction in One-Way Delay (OWD) rates in the communication between IoT devices mediated by brokers found at the fog and edge levels.
The Internet of Things (IoT) is an emerging computing paradigm that supports the interconnection of objects. With the rapid growth in smart technologies, IoT is gaining popularity from industry and academia focusing on communication and networking of smart objects. It is assumed that in a typical IoT application, the smart sensors are capable of directly delivering a service with no or minimal human involvement. There are many new technologies that are driving the development of IoT, which include cloud computing, wireless sensor networks, and 5G, etc. On the other hand, there are many research challenges that need to be addressed such as identity management of billions of devices connected to the internet, standardization, privacy, energy management, security of the information, space to store and process the information, etc. In this regard, the main focus of this chapter is to present IoT in a broader perspective and its associated technologies and applications along with a review of the work published in these areas.
Artificial intelligence technology is applied in numerous fields. Several countries around the world have introduced national policies on artificial intelligence, and the competition for this emerging technology has become an important driving force for industrial development. In recent years, interdisciplinary research on artificial intelligence has made great progress. From the perspective of idea‐driven technology entrepreneurship, we discuss the concept of AI with other emerging technologies. For the early stage of the entrepreneurial process, from idea generation to entrepreneurial opportunity exploitation, we elaborate on the role played by AI. Finally, the future research prospects are proposed.
Nano Fiber production techniques and Nano particle for functional product developments
4G networks (with Internet Protocol or IP, telecommunications and reaction‐based connectivity) have managed the network architecture. They have evolved and are now accessible in a multitude of ways, including advanced learning and deep learning. 5G is flexible and responsive and will establish the need for integrated real time decision‐making. As the rollout has begun across the globe, recent technical and architectural developments in 5G networks have proved their value. In various fields of classification, recognition and automation, AI has already proved its efficacy with greater precision. The integration of artificial intelligence with internet‐connected computers and superfast 5G wireless networks opens up possibilities around the globe and even in outer space. In this section, we offer an in‐depth overview of the Artificial Intelligence implementation of 5G wireless communication systems. The focus of this research is in this context, to examine the application of AI and 5G in warehouse building and to discuss the role and difficulties faced, and to highlight suggestions for future studies on integrating Advanced AI in 5G wireless communications.
Modern networks generate a massive amount of traffic data streams. Analysing this data is essential for various purposes, such as network resources management and cyber-security analysis. There is an urgent need for data analytic methods that can perform network data processing in an online manner based on the arrival of new data. Online machine learning (OL) techniques promise to support such type of data analytics. In this
paper, we investigate and compare those OL techniques that facilitate data
stream analytics in the networking domain. We also investigate the importance of traffic data analytics and highlight the advantages of online learning
in this regard, as well as the challenges associated with OL-based network
traffic stream analysis, e.g., concept drift and the imbalanced classes. We
review the data stream processing tools and frameworks that can be used to
process such data online or on-the-fly along with their pros and cons, and
their integrability with de facto data processing frameworks. To explore the
performance of OL techniques, we conduct an empirical evaluation on the
performance of different ensemble- and tree-based algorithms for network
traffic classification. Finally, the open issues and the future directions in
analysing traffic data streams are presented. This technical study presents
valuable insights and outlook for the network research community when dealing with the requirements and purposes of online data streams analytics and
learning in the networking domain.
Network densification through the deployment of small cells along the coverage area of a macro-cell, employing massive multiple input multiple output (MIMO) and millimeter-wave (mmWave) technologies, is a key approach to enhancing the network capacity and coverage of future systems. For ultra-dense mmWave heterogeneous scenarios with a massive number of users, one should address both inter- and intra-tier interferences contrary to the low-density scenarios where the network is mainly noise-limited. Therefore, this paper proposes low complex hybrid analog-digital receive and transmit beamforming techniques for ultra-dense uplink massive MIMO mmWave heterogeneous systems to efficiently mitigate these interferences. At the small cells, the hybrid analog-digital receive beamforming/equalizer is computed in a distributed fashion, where the analog processing is performed at the small cell base stations or access points and the digital part at a central unit for joint processing. To optimize the analog part of the hybrid equalizer and the precoders used at the user terminals, we consider as a metric the distance relative to the fully digital counterpart induced by the Frobenius norm. In the optimization problem, apart from the analog constraints usually considered in the homogeneous systems, we further impose the constraints inherent to the distributed nature of the access points. To cancel the inter-tier interference, the digital parts of the precoders employed at the small cell user terminals are designed so that this interference resides in a low dimension subspace at the macro base station. The results show that the performance of the proposed hybrid analog-digital precoder/equalizer scheme is close to the fully digital counterpart and is able to efficiently remove both inter- and intra-tier interferences.
Written by leading experts in 5G research, this book is a comprehensive overview of the current state of 5G. Covering everything from the most likely use cases, spectrum aspects, and a wide range of technology options to potential 5G system architectures, it is an indispensable reference for academics and professionals involved in wireless and mobile communications. Global research efforts are summarised, and key component technologies including D2D, mm-wave communications, massive MIMO, coordinated multi-point, wireless network coding, interference management and spectrum issues are described and explained. The significance of 5G for the automotive, building, energy, and manufacturing economic sectors is addressed, as is the relationship between IoT, machine type communications, and cyber-physical systems. This essential resource equips you with a solid insight into the nature, impact and opportunities of 5G.
The IoT paradigm holds the promise to revolutionize the way we live and work by means of a wealth of new services, based on seamless interactions between a large amount of heterogeneous devices. After decades of conceptual inception of the IoT, in recent years a large variety of communication technologies has gradually emerged, reflecting a large diversity of application domains and of communication requirements. Such heterogeneity and fragmentation of the connectivity landscape is currently hampering the full realization of the IoT vision, by posing several complex integration challenges. In this context, the advent of 5G cellular systems, with the availability of a connectivity technology, which is at once truly ubiquitous, reliable, scalable, and cost-efficient, is considered as a potentially key driver for the yet-to emerge global IoT. In the present paper, we analyze in detail the potential of 5G technologies for the IoT, by considering both the technological and standardization aspects. We review the present-day IoT connectivity landscape, as well as the main 5G enablers for the IoT. Last but not least, we illustrate the massive business shifts that a tight link between IoT and 5G may cause in the operator and vendors ecosystem.
This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.
What will 5G be? What it will not be is an incremental advance on 4G. The
previous four generations of cellular technology have each been a major
paradigm shift that has broken backwards compatibility. And indeed, 5G will
need to be a paradigm shift that includes very high carrier frequencies with
massive bandwidths, extreme base station and device densities and unprecedented
numbers of antennas. But unlike the previous four generations, it will also be
highly integrative: tying any new 5G air interface and spectrum together with
LTE and WiFi to provide universal high-rate coverage and a seamless user
experience. To support this, the core network will also have to reach
unprecedented levels of flexibility and intelligence, spectrum regulation will
need to be rethought and improved, and energy and cost efficiencies will become
even more critical considerations. This paper discusses all of these topics,
identifying key challenges for future research and preliminary 5G
standardization activities, while providing a comprehensive overview of the
current literature, and in particular of the papers appearing in this special
issue.
Full-Duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) and beyond wireless communication systems due to its advantages including potential doubling of the capacity and increased spectrum utilization efficiency. However, one of the main challenges of the FD technology is the mitigation of strong Self-Interference (SI). Recent advances in different SI cancellation techniques such as antenna cancellation, analog cancellation and digital cancellation methods have led to the feasibility of using FD technology in different wireless applications. Among potential applications, one important application area is Dynamic Spectrum Sharing (DSS) in wireless systems particularly 5G networks, where FD can provide several benefits and possibilities such as Concurrent Sensing and Transmission (CST), Concurrent Transmission and Reception (CTR), improved sensing efficiency and secondary throughput, and the mitigation of the hidden terminal problem. In this direction, first, starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems.
Spectrum efficiency is one of the key performance metrics in 5G communication networks. To enhance spectrum efficiency, advanced spectrum sharing techniques are normally used. In this article, we provide a survey of the recent development of advanced techniques for spectrum sharing. In particular, we elaborate cognitive radio, device-todevice communication, in-band full-duplex communication, non-orthogonal multiple access, and Long Term Evolution on unlicensed spectrum. For each technique, we present the basic principle and research methodology of the state of the art. By considering various promising evolutions in 5G networks, we emphasize challenges to deploy each technique. Finally, we discuss the integration issue of multiple spectrum sharing techniques and identify potential challenges.
Recent research and technology trends are shifting toward IoT and CRNs. However, we think that the things-oriented, Internet-oriented, and semantic-oriented versions of IoT are meaning- less if IoT objects are not equipped with cogni- tive radio capability. Equipping IoT objects with CR capability has lead to a new research dimen- sion of CR-based IoT. In this article, we present an overview of CR-based IoT systems. We high- light potential applications of CR-based IoT sys- tems. We survey architectures and frameworks of CR-based IoT systems. We furthermore discuss spectrum-related functionalities for CR-based IoT systems. Finally, we present open issues and research challenges faced by CR-based IoT net- works along with future directions.
5G cellular networks are assumed to be the key enabler and infrastructure provider in the ICT industry, by offering a variety of services with diverse requirements. The standardization of 5G cellular networks is being expedited, which also implies more of the candidate technologies will be adopted. Therefore, it is worthwhile to provide insight into the candidate techniques as a whole and examine the design philosophy behind them. In this article, we try to highlight one of the most fundamental features among the revolutionary techniques in the 5G era, i.e., there emerges initial intelligence in nearly every important aspect of cellular networks, including radio resource management, mobility management, service provisioning management, and so on. However, faced with ever-increasingly complicated configuration issues and blossoming new service requirements, it is still insufficient for 5G cellular networks if it lacks complete AI functionalities. Hence, we further introduce fundamental concepts in AI and discuss the relationship between AI and the candidate techniques in 5G cellular networks. Specifically, we highlight the opportunities and challenges to exploit AI to achieve intelligent 5G networks, and demonstrate the effectiveness of AI to manage and orchestrate cellular network resources. We envision that AI-empowered 5G cellular networks will make the acclaimed ICT enabler a reality.
Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for performance enhancement in next-generation cellular communications. Compared to orthogonal frequency division multiple access (OFDMA), which is a well-known high-capacity orthogonal multiple access (OMA) technique, NOMA offers a set of desirable benefits, including greater spectrum efficiency. There are different types of NOMA techniques, including power-domain and code-domain. This paper primarily focuses on power-domain NOMA that utilizes superposition coding (SC) at the transmitter and successive interference cancellation (SIC) at the receiver. Various researchers have demonstrated that NOMA can be used effectively to meet both network-level and user-experienced data rate requirements of fifth-generation (5G) technologies. From that perspective, this paper comprehensively surveys the recent progress of NOMA in 5G systems, reviewing the state-of-the-art capacity analysis, power allocation strategies, user fairness, and user-pairing schemes in NOMA. In addition, this paper discusses how NOMA performs when it is integrated with various proven wireless communications techniques, such as cooperative communications, multiple input multiple output (MIMO), beamforming, space time coding, and network coding, among others. Furthermore, this paper discusses several important issues on NOMA implementation and provides some avenues for future research.
The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, etc. The Internet of Things (IoT) offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while the IoT devices continue to grow in both numbers and their requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low power devices and its related challenges. We detail two case studies, the first one targets energy-efficient scheduling in smart homes and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities.
The Internet of things (IoT) is emerging as a popular future Internet paradigm, in which physical entities and cyber entities are connected to form a network of networks. It is expected to enable mass participation of " things " on mission critical services such as energy, mobility, healthcare, to name a few. Therefore, it is a matter of time for the IoT network to grow to billions of connected nodes. This leads to a variety of new, as well as existent, potential security risks whose severity depends on the environment in which the Internet of things is deployed. This paper categorizes the major components in the IoT domain and provides a classification of security requirements and security threats applicable to each component. It also discusses open security problems and provides directions for future research in order to address scalability and efficiency concerns, while allowing seamless introduction of new applications in this domain.