Challenges Of Internet Research Articles

Research Challenges in Internet Ad Markets: Vignettes on Complex Environments

Internet ad markets have been a great source of motivation and challenging problems for the Economics and Computation community. The practical design of these ad markets has also greatly benefited from advances in the Economics and Computation community. Through a series of vignettes, we aim to highlight interesting challenges in modern internet ad markets, born out of a Google perspective. In this first article, we focus on a few particular auction design and optimization questions motivated by the Sponsored Search and Display Ads markets. We hope these articles spur further progress in the research community and in industry.

WEB SECURITY: A QUICK START INTRODUCTION TO OAUTH 2.0 AND KEYCLOAK 19.X AUTHORIZATION SCENARIOS

OAuth 2.0 (Hardt, 2012) (note 1) is a widely used web security protocol. The aim of this paper is to illustrate OAuth 2.0 procedures by the use of Keycloak authorization server (Thorgensen, 2021) (note 6). Since OAuth 2.0 is a broad subject, we focus on selected Best Current Practice (BCP) topics, including the common types of authorization flows, and on the key aspects of bearer token processing by the protected resource server. The evolution of OAuth 2.0 towards OAuth version 2.1 implied by new internet challenges is also briefly discussed. To illustrate OAuth 2.0 procedures, we use a .NET6/C# demo implementation of client and server HTTP components, utilizing thereby well-known .NET6/C# classes such as HttpClient and HttpListener.

University students' perspectives on the benefits and challenges of emergency remote teaching during the Covid-19 pandemic in Ghana.

The advent of Covid-19 changed how education is carried out at the tertiary level in Ghana. Despite the lunch of emergency remote teaching at the University of Ghana in 2020, little research has been done on students' experiences. Using a qualitative descriptive design, this study explored students' experiences regarding the benefits, challenges, and the influence of emergency remote teaching on their self-esteem, academic confidence, and performance. 20 students were interviewed, and their responses were analyzed using thematic analysis. Results showed students had both positive and negative experiences which had diverse impacts on their self-esteem, academic confidence, and performance. Positive experiences resulted from the confidence to participate in class without intimidation, improved IT literacy, self-esteem and academic performance, less distraction and leniency from lecturers. Negative experiences bothered on problems with the learning management system, internet challenges, laziness on the part of students, high cost of internet data, unconducive learning environment, comprehension difficulties, increased workload and cheating by students. The findings underscore the need for university management to consider students' psychological wellbeing and needs when implementing new educational systems and further put measures in place to improve emergency remote teaching and curb academic dishonesty in order to improve tertiary education in Ghana amidst Covid-19.

A Rateless 16QAM Scheme for IoT Uplink Communications

How to achieve a high transmission rate at a low cost of energy consumption in a wide range of channel variations is a critical challenge in Internet of Things (IoT) applications. In this article, a rateless 16 quadrature amplitude modulation (R-16QAM) scheme for IoT uplink communications is proposed to deal with this problem. The R-16QAM transmitter consists of an encoder, a random bit selector, and a tailored modulation mapper. Different from the sequential bits selection and Gary mapping in conventional 16QAM modulation, bits are randomly selected and mapped into a 16QAM symbol by a weighted summation of selected bits in R-16QAM. The random bits selection introduces correlation among modulated symbols, enabling the transmitter to work in a rateless manner, i.e., the transmitter keeps generating and sending R-16QAM symbols until a feedback of successful decoding is received from the receiver. It means that the number of symbols transmitted varies with channel variations. In this way, the proposed R-16QAM can automatically adjust to channel conditions and work well in a wide range of channel conditions. The weighted-summation mapping can be illustrated by a “Tanner graph,” based on which we develop a low complexity iterative demodulation algorithm to improve receiver performance. The simulations show that compared with narrow band Internet of Things (NB-IoT) standard and Turbo coded light-weight rate compatible modulation (TLRCM) for IoT uplink communications, the proposed R-16QAM scheme can consistently achieve a lower energy consumption in a signal-to-noise-ratio (SNR) range of −10–15 dB. Moreover, it can achieve a maximum transmission throughput of 3.96 bits/s/Hz at SNR=15 dB while only 0.66 and 1.7 bits/s/Hz are achieved in NB-IoT and TLRCM, respectively. These advantages enable the proposed R-16QAM scheme to be particularly suitable to IoT application scenarios where nodes work with limit energy resources under a large range of channel variations.

Challenges in internet of things towards the security using deep learning techniques

Securing IoT devices and delivering end-to-end security in an IoT ecosystem presents a variety of issues. Regardless of the way that security concerns are not new with regards to data innovation, the qualities of numerous IoT arrangements give new and special security issues. It's anything but a main concern to resolve these issues and guarantee the security of IoT items and administrations. Clients should have certainty that IoT gadgets and related information administrations are secure, especially as this innovation develops more unavoidable and coordinated into our day by day lives. The goal of this article is to provide an overview of the Internet of Things and to go through all of the known security concerns that the Internet of Things faces today. All of the findings are based on publicly available documentation for essential Internet of Things components. Threats to IoT security, both inherent and newly developed, are discussed, as well as numerous potentials. The attack surfaces of the IoT system are examined, as well as the potential hazards associated with each surface. We then, at that point go over the benefits, weaknesses, and qualities of every Deep Learning approach for IoT security. We talk about the advantages and disadvantages of applying Deep Learning to IoT security. Future exploration headings could be founded on these chances and difficulties.

Approaches and Challenges in Internet of Robotic Things

The Internet of robotic things (IoRT) is the combination of different technologies including cloud computing, robots, Internet of things (IoT), artificial intelligence (AI), and machine learning (ML). IoRT plays a major role in manufacturing, healthcare, security, and transport. IoRT can speed up human development by a very significant percentage. IoRT allows robots to transmit and receive data to and from other devices and users. In this paper, IoRT is reviewed in terms of the related techniques, architectures, and abilities. Consequently, the related research challenges are presented. IoRT architectures are vital in the design of robotic systems and robotic things. The existing 3–7-tier IoRT architectures are studied. Subsequently, a detailed IoRT architecture is proposed. Robotic technologies provide the means to increase the performance and capabilities of the user, product, or process. However, robotic technologies are vulnerable to attacks on data security. Trust-based and encryption-based mechanisms can be used for secure communication among robotic things. A security method is recommended to provide a secure and trustworthy data-sharing mechanism in IoRT. Significant security challenges are also discussed. Several known attacks on ad hoc networks are illustrated. Threat models ensure integrity confidentiality and availability of the data. In a network, trust models are used to boost a system’s security. Trust models and IoRT networks play a key role in obtaining a steady and nonvulnerable configuration in the network. In IoRT, remote server access results in remote software updates of robotic things. To study navigation strategies, navigation using fuzzy logic, probabilistic roadmap algorithms, laser scan matching algorithms, heuristic functions, bumper events, and vision-based navigation techniques are considered. Using the given research challenges, future researchers can get contemporary ideas of IoRT implementation in the real world.

Interference Management in Cellular-Connected Internet of Drones Networks With Drone-Pairing and Uplink Rate-Splitting Multiple Access

Interference management is a key challenge for cellular-connected Internet of Drones (IoD) networks that employ multiple cellular-connected hovering drones for data acquisition in surveillance and monitoring applications. This article proposes a novel resource optimization framework for managing interference in cellular-connected IoD networks. Specifically, the envisioned system divides the set of transmitting drones into distinct drone pairs, where the paired drones simultaneously transmit over the same radio resource blocks (RRBs). Each drone pair is assigned a set of orthogonal RRBs for data transmission, where these RRBs are shared with the terrestrial cellular network as well. An uplink rate-splitting multiple access scheme is employed to mitigate the interdrone interference at the drone pairs, and an RRB pricing method is exploited to control the interference between the aerial and cellular communication links. Our goal is to maximize the uplink capacity of the IoD network while reducing interference over the shared RRBs between the IoD and cellular networks. Toward this goal, a joint optimization of the drones’ transmit power allocation, drone pairing, and RRB scheduling among the drone pairs is presented. In order to obtain an efficient suboptimal solution, an iterative optimization is devised. Particularly, the presented joint optimization problem is decomposed into three subproblems for transmit power allocation, drone pairing and RRB scheduling, and RRB price update. By solving theses subproblems iteratively, a convergent rate-splitting-empowered resource allocation and clustering for interference management (REACT) algorithm is proposed. Extensive simulations are conducted to verify the effectiveness of the proposed REACT algorithm over several benchmark schemes.

A Comprehensive Study with Challenges of Internet of Things (IoT) based Model for Smart Farming

A Comprehensive Study with Challenges of Internet of Things (IoT) based Model for Smart Farming

A Cognitive Routing Framework for Reliable Communication in IoT for Industry 5.0

Industry 5.0 requires intelligent self-organi- zed, self-managed, and self-monitoring applications with ability to analyze and predict the human as well as machine behaviors across interconnected devices. Tackling dynamic network behavior is a unique challenge for Internet of Things applications in Industry 5.0. Knowledge-defined networks (KDN) bridge this gap by extending software-defined networking architecture with knowledge plane, which learns the network dynamics to avoid suboptimal decisions. Cognitive routing leverages the sixth-generation (6G) self-organized networks with self-learning feature. This article presents a self-organized cognitive routing framework for a KDN which uses link-reliability as a routing metric. It reduces end-to-end latency by choosing the most reliable path with minimal probability of route-flapping. The proposed framework precalculates all possible paths between every pair of nodes and ensures self-healing with a constant-time convergence. An experimental test-bed has been developed to benchmark the proposed framework against the industry-stranded link-state and distance-vector routing algorithms SPF and DUAL, respectively.

EVOLUTION AND ANALYSIS OF SECURED HASH ALGORITHM (SHA) FAMILY

With the rapid advancement of technologies and proliferation of intelligent devices, connecting to the internet challenges have grown manifold, such as ensuring communication security and keeping user credentials secret. Data integrity and user privacy have become crucial concerns in any ecosystem of advanced and interconnected communications. Cryptographic hash functions have been extensively employed to ensure data integrity in insecure environments. Hash functions are also combined with digital signatures to offer identity verification mechanisms and non-repudiation services. The federal organization National Institute of Standards and Technology (NIST) established the SHA to provide security and optimal performance over some time. The most well-known hashing standards are SHA-1, SHA-2, and SHA-3. This paper discusses the background of hashing, followed by elaborating on the evolution of the SHA family. The main goal is to present a comparative analysis of these hashing standards and focus on their security strength, performance and limitations against common attacks. The complete assessment was carried out using statistical analysis, performance analysis and extensive fault analysis over a defined test environment. The study outcome showcases the issues of SHA-1 besides exploring the security benefits of all the dominant variants of SHA-2 and SHA-3. The study also concludes that SHA-3 is the best option to mitigate novice intruders while allowing better performance cost-effectively.

Exploring Educational Technologies Used by Mthwakazi University Rural Satellite Campuses to Implement Distance Teacher Education Programmes

The 21st century has seen a massive advent of technologies, arguably more than any other time in the history of humankind. Education systems worldwide have embraced emerging technologies to expedite their teaching and learning systems to stay abreast and relevant to the time. The study explored the types of educational technologies used by Mthwakazi University (MU) rural satellite campuses to implement distance teacher education programmes. An interpretive research paradigm was employed using a qualitative research approach and a case study design. Interviews were used to gather data from six purposively selected lecturers at MU rural satellite campuses. Data was analysed narratively under emerging themes. Findings concluded that lecturers at MU rural satellite campuses used limited educational technologies, mostly traditional paper and text, due to electricity and internet challenges and lecturers’ lack of ICT skills and knowledge. The study recommended that MU rural satellite campuses should use flash drives, Compact Disks (CDs) and Digital Versatile/Video Disks (DVDs) to download Encarta, encyclopedia and updated information and upload it into computers for access by students, invest in alternative internet sources like dongles and wireless mobile networks like ECONET and MTN.

Viewpoints on the Experiences and Challenges of Fishery Energy Internet

Viewpoints on the Experiences and Challenges of Fishery Energy Internet

Role and challenges of internet of things and informatics in Healthcare research

Role and challenges of internet of things and informatics in Healthcare research

Drivers and challenges of internet of things diffusion in smart stores: A field exploration

The digitally disruptive environment has evolved rapidly due to the introduction of new advancements within the field of smart applications. Applications of one of the most prominent technologies, Internet of Things (IoT), often appear in the retail sector, where smart services have transformed the customer experience holistically. Presented in this paper are the findings from an exploratory field study in the retail service sector, which drew on the views of experienced practitioners about the smart store experience and the associated changes. The paper presents an overview of the drivers of smart retail service diffusion and the relevant challenges, such as the business expectations and the heterogeneity of devices. The arising themes indicate that IoT security is a major challenge for businesses installing IoT devices in their journey towards smart store transformation. The paper highlights the importance of a secure data-sharing IoT environment that respects customer privacy as the smart experience in-store offers data-driven insights and services. Implications for research and practice are discussed in terms of the customer experience relevant to the identified challenges.

Artificial intelligence Internet of Things: A new paradigm of distributed sensor networks

The advances and convergence in sensor, information processing, and communication technologies have shaped the Internet of Things of today. The rapid increase of data and service requirements brings new challenges for Internet of Thing. Emerging technologies and intelligent techniques can play a compelling role in prompting the development of intelligent architectures and services in Internet of Things to form the artificial intelligence Internet of Things. In this article, we give an introduction and review recent developments of artificial intelligence Internet of Things, the various artificial intelligence Internet of Things computational frameworks and highlight the challenges and opportunities for effective deployment of artificial intelligence Internet of Things technology to address complex problems for various applications. This article surveys the recent developments and discusses the convergence of artificial intelligence and Internet of Things from four aspects: (1) architectures, techniques, and hardware platforms for artificial intelligence Internet of Things; (2) sensors, devices, and energy approaches for artificial intelligence Internet of Things; (3) communication and networking for artificial intelligence Internet of Things; and (4) applications for artificial intelligence Internet of Things. The article also discusses the combination of smart sensors, edge computing, and software-defined networks as enabling technologies for the artificial intelligence Internet of Things.

Design of Relay Switching to Combat an Eavesdropper in IoT-NOMA Wireless Networks

The requirements of low latency, low cost, less energy consumption, high flexibility, high network capacity, and high data safety are crucial challenges for future Internet of Things (IoT) wireless networks. Motivated by these challenges, this study deals with a novel design of green-cooperative IoT network, which employed coupled relays consisting of one IoT relay selected for forwarding signals to multiple IoT devices while another IoT relay transmitted jamming signals to an eavesdropper. For flexibility, all IoT nodes were powered by solar energy enough to sustain themselves, in order to consume less energy. To reach low latency, the study adopted the emerging non-orthogonal multiple access technique to serve multiple IoT devices simultaneously. Furthermore, the study adopted the simultaneous wireless information and power transfer technique which transmits wireless data for information processing and energy for energy harvesting. The study sketched a novel transmission block time period framework which plotted how a signal could travel via an individual IoT model. Maximizing the achievable bit-rate of IoT devices was considered to improve network capacity and data safety as well. Aiming at enhancing secrecy performance, a rest IoT relay played a role as a friendly jammer to transmit a jamming signal to an eavesdropper using energy harvested from the power splitting protocol. The results achieved in this study showed that the proposed model satisfied the requirements of future green IoT wireless networks. Derivatives leading to closed-form expressions are presented and verified by simulation results. The investigated results demonstrated that a friendly jammer based on radio frequency and energy harvesting strongly forces the intercept probability performance of the eavesdropper towards one, while outage probability performance of IoT devices towards zero showed that the signal to noise ratio tends to infinity.

Edge Computing Application, Architecture, and Challenges in Ubiquitous Power Internet of Things

The Ubiquitous Power Internet of Things (UPIoT) is a concrete manifestation of the Internet of things (IoT) in the power industry, which is a deep integration of the interconnected power network and communication network, realizing full perception of the system status and full business penetration in all links of power production, transmission, and consumption. The introduction of edge computing in UPIoT fully meets the requirements of rapid response, real-time perception, and to some extent, privacy protection. However, there is currently no comprehensive investigation on the application of edge computing technology in UPIoT. First, this paper introduces the development background and construction of UPIoT and its technical architecture. Then the challenges faced by UPIoT in the process of construction are analyzed. Furthermore, the paper elaborates on the functions and features of edge computing, proposes that the support of edge computing technology can solve the challenges of efficient, fast, and secure processing of massive edge data faced by the traditional cloud-based centralized big data processing technology of UPIoT, and analyzes the architecture of the edge computing-assisted UPIoT. For the three typical scenarios of UPIoT, namely power monitoring system, smart energy system and power metering system, the edge computing architecture of the three scenarios are analyzed, and the specific application methods and roles played by edge computing in the three scenarios are also elaborated. Finally, we discuss the challenges of edge computing in UPIoT, in terms of policy challenges, market challenges, and technical challenges, as well as outline the outlooks of the technical challenges.

Visible Light Communications for Internet of Things: Prospects and Approaches, Challenges, Solutions and Future Directions

Visible light communications (VLC) is an emerging and promising concept that is capable of solving the major challenges of 5G and Internet of Things (IoT) communication systems. Moreover, due to the usage of light-emitting diodes (LEDs) in almost every aspect of our daily life VLC is providing massive connectivity for various types of massive IoT communications ranging from machine-to-machine, vehicle-to-infrastructure, infrastructure-to-vehicle, chip-to-chip as well as device-to-device. In this paper, we undertake a comprehensive review of the prospects of implementing VLC for IoT. Moreover, we investigate existing and proposed approaches implemented in the application of VLC for IoT. Additionally, we look at the challenges faced in applying VLC for IoT and offer solutions where applicable. Then, we identify future research directions in the implementation of VLC for IoT.

A secure framework for IoT-based smart climate agriculture system: Toward blockchain and edge computing

Abstract An intelligent climate and watering agriculture system is presented that is controlled with Android application for smart water consumption considering small and medium ruler agricultural fields. Data privacy and security as a big challenge in current Internet of Things (IoT) applications, as with the increase in number of connecting devices, these devices are now more vulnerable to security threats. An intelligent fuzzy logic and blockchain technology is implemented for timely analysis and securing the network. The proposed design consists of various sensors that collect real-time data from environment and field such as temperature, soil moisture, light intensity, and humidity. The sensed field information is stored in IoT cloud platform, and after the analysis of entries, watering is scheduled by implementing the intelligent fuzzy logic and blockchain. The intelligent fuzzy logic based on different set of rules for making smart decisions to meet the watering requirements of plant and blockchain technology provides necessary security to the IoT-enabled system. The implementation of blockchain technology allows access only to the trusted devices and manages the network. From the experimentation, it is observed that the proposed system is highly scalable and secure. Multiple users at the same time can monitor and interact with the system remotely by using the proposed intelligent agricultural system. The decisions are taken by applying intelligent fuzzy logic based on input variables, and an alert is transmitted about watering requirements of a field to the user. The proposed system is capable of notifying users for turning water motor on and off. The experimental outcomes of the proposed system also reveal that it is an efficient and highly secure application, which is capable of handling the process of watering the plants.

Collaborative Edge Computing for Social Internet of Things: Applications, Solutions, and Challenges

The paradigm of Internet of Things (IoT) has attracted much attention in both academia and industry areas in the past decades. Recently, the integration of IoT and social networks is advocated to promote further development. This article focuses on the applications, solutions, and challenges of Social Internet of Things (SIoT) over collaborative edge computing, which exploits the advantages of both mobile edge computing and social relationships among SIoT users. First, applications of collaborative offloading, caching, and streaming data processing are illustrated, followed by representative social-aware solutions, including auction, coalition game, and federated learning. Finally, several research challenges are described. The main contributions of this article are as follows: 1) we specify the role of social ties in traditional applications of IoT and its impacts on individual’s selection; 2) we elaborate the reasons why the presented three approaches can be applied in SIoT; and 3) the discussed challenges can contribute to the future development of secure, robust, and intelligent SIoT frameworks.