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Future Internet, Volume 15, Issue 2 (February 2023) – 46 articles

Cover Story (view full-size image): In the metaverse, the physical world is seamlessly integrated with the cyber world via real-time digitization of physical objects. The metaverse enables new forms of immersive experiences but is posing significant challenges due to high resource demands. To tackle these challenges, a flexible mobility-aware request assignment and resource allocation framework with efficient processing is proposed by anchoring decomposed metaverse augmented reality services at different edge nodes and proactively caching background metaverse region models embedded with target augmented-reality objects. Numerical investigations reveal the benefits of the proposed mobility-aware optimization problem that balances service delay and energy consumption under the constraints of perceived user quality. View this paper
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17 pages, 14648 KiB  
Article
Diabetes Monitoring System in Smart Health Cities Based on Big Data Intelligence
by Shadi AlZu’bi, Mohammad Elbes, Ala Mughaid, Noor Bdair, Laith Abualigah, Agostino Forestiero and Raed Abu Zitar
Future Internet 2023, 15(2), 85; https://doi.org/10.3390/fi15020085 - 20 Feb 2023
Cited by 5 | Viewed by 3144
Abstract
Diabetes is a metabolic disorder in which the body is unable to properly regulate blood sugar levels. It can occur when the body does not produce enough insulin or when cells become resistant to insulin’s effects. There are two main types of diabetes, [...] Read more.
Diabetes is a metabolic disorder in which the body is unable to properly regulate blood sugar levels. It can occur when the body does not produce enough insulin or when cells become resistant to insulin’s effects. There are two main types of diabetes, Type 1 and Type 2, which have different causes and risk factors. Early detection of diabetes allows for early intervention and management of the condition. This can help prevent or delay the development of serious complications associated with diabetes. Early diagnosis also allows for individuals to make lifestyle changes to prevent the progression of the disease. Healthcare systems play a vital role in the management and treatment of diabetes. They provide access to diabetes education, regular check-ups, and necessary medications for individuals with diabetes. They also provide monitoring and management of diabetes-related complications, such as heart disease, kidney failure, and neuropathy. Through early detection, prevention and management programs, healthcare systems can help improve the quality of life and outcomes for people with diabetes. Current initiatives in healthcare systems for diabetes may fail due to lack of access to education and resources for individuals with diabetes. There may also be inadequate follow-up and monitoring for those who have been diagnosed, leading to poor management of the disease and lack of prevention of complications. Additionally, current initiatives may not be tailored to specific cultural or demographic groups, resulting in a lack of effectiveness for certain populations. In this study, we developed a diabetes prediction system using a healthcare framework. The system employs various machine learning methods, such as K-nearest neighbors, decision tree, deep learning, SVM, random forest, AdaBoost and logistic regression. The performance of the system was evaluated using the PIMA Indians Diabetes dataset and achieved a training accuracy of 82% and validation accuracy of 80%. Full article
(This article belongs to the Special Issue Smart Objects and Technologies for Social Good II)
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19 pages, 8034 KiB  
Article
Development of a Vision-Based Unmanned Ground Vehicle for Mapping and Tennis Ball Collection: A Fuzzy Logic Approach
by Masoud Latifinavid and Aydin Azizi
Future Internet 2023, 15(2), 84; https://doi.org/10.3390/fi15020084 - 19 Feb 2023
Cited by 10 | Viewed by 2559
Abstract
The application of robotic systems is widespread in all fields of life and sport. Tennis ball collection robots have recently become popular because of their potential for saving time and energy and increasing the efficiency of training sessions. In this study, an unmanned [...] Read more.
The application of robotic systems is widespread in all fields of life and sport. Tennis ball collection robots have recently become popular because of their potential for saving time and energy and increasing the efficiency of training sessions. In this study, an unmanned and autonomous tennis ball collection robot was designed and produced that used LiDAR for 2D mapping of the environment and a single camera for detecting tennis balls. A novel method was used for the path planning and navigation of the robot. A fuzzy controller was designed for controlling the robot during the collection operation. The developed robot was tested, and it successfully detected 91% of the tennis balls and collected 83% of them. Full article
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37 pages, 2254 KiB  
Review
Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods
by Tehseen Mazhar, Hafiz Muhammad Irfan, Sunawar Khan, Inayatul Haq, Inam Ullah, Muhammad Iqbal and Habib Hamam
Future Internet 2023, 15(2), 83; https://doi.org/10.3390/fi15020083 - 19 Feb 2023
Cited by 25 | Viewed by 7528
Abstract
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of [...] Read more.
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receiving data packets over the network. Cyberattacks can compromise the smart grid’s dependability, availability, and privacy. Users, the communication network of smart devices and sensors, and network administrators are the three layers of an innovative grid network vulnerable to cyberattacks. In this study, we look at the many risks and flaws that can affect the safety of critical, innovative grid network components. Then, to protect against these dangers, we offer security solutions using different methods. We also provide recommendations for reducing the chance that these three categories of cyberattacks may occur. Full article
(This article belongs to the Special Issue Cybersecurity in the Era of AI)
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23 pages, 884 KiB  
Article
Optimal Pricing in a Rented 5G Infrastructure Scenario with Sticky Customers
by Marta Flamini and Maurizio Naldi
Future Internet 2023, 15(2), 82; https://doi.org/10.3390/fi15020082 - 19 Feb 2023
Viewed by 974
Abstract
The ongoing deployment of 5G is accompanied by architecture and pricing decisions. Network sharing is a critical feature, allowing operators to reduce their costs, but introducing a mixed partnering/competition situation, where the infrastructure owner, renting out their infrastructure to virtual operators (who act [...] Read more.
The ongoing deployment of 5G is accompanied by architecture and pricing decisions. Network sharing is a critical feature, allowing operators to reduce their costs, but introducing a mixed partnering/competition situation, where the infrastructure owner, renting out their infrastructure to virtual operators (who act as customers), also provides services to end customers, competing with virtual operators. Pricing is the leverage through which an optimal balance between the two roles is accomplished. However, pricing may not be the only variable affecting customers’ choice, which may prefer (stick to) one operator for several reasons. In this paper, we formulate a game model to analyse the optimal pricing decisions for operators in the presence of such sticky behaviour of customers. After concluding that the game does not allow for a Nash equilibrium, we consider a case when one of the parties (the infrastructure owner, the virtual operators, or the regulator) is responsible for setting prices and analyse how operators’ profits are impacted when price-setting powers are shifted among the parties. The scenario where the regulator sets prices leads to the lowest profits for the operators, even lower than when competitors set prices. Full article
(This article belongs to the Special Issue Network Cost Reduction in Cloud and Fog Computing Environments)
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17 pages, 2443 KiB  
Review
Research Trends of the Internet of Things in Relation to Business Model Innovation: Results from Co-Word and Content Analyses
by Atik Kulakli and Cenk Lacin Arikan
Future Internet 2023, 15(2), 81; https://doi.org/10.3390/fi15020081 - 17 Feb 2023
Cited by 3 | Viewed by 1948
Abstract
In the era of the Internet of Things, innovative business model initiatives continue to deepen, and the trend of search domains continues to expand. This paper aims to scientifically analyze research trends of the Internet of Things in relation to Business Model Innovation [...] Read more.
In the era of the Internet of Things, innovative business model initiatives continue to deepen, and the trend of search domains continues to expand. This paper aims to scientifically analyze research trends of the Internet of Things in relation to Business Model Innovation through bibliometric studies. The data were collected using the Clarivate Web of Science (WoS) Core Collection (SSCI and SCI indexed) from 2005 to 2022 (November). However, the publications for the research domains started in 2015. The results show that scientific publications on the Internet of Things in relation to Business Model Innovation have increased gradually since 2019. The WoS database is utilized for analyses because it contains journals and conference proceedings deemed more relevant by the academic domain and highly reputable sources for bibliometric studies. The VOS viewer, R Language, and Microsoft Excel were also used to analyze and complete the study. Bibliometric and scientometric analyses were conducted to identify publication patterns, text analysis, most important keywords (co-word, word cloud, and co-occurrence), trends for the topicality, and content clustering for the publication periods. The visualization of the research trends of the Internet of Things in relation to Business Model Innovation resulted in four co-occurrence clusters leading to some of the topic areas mentioned as follows: (1) The Internet of Things, (2) Business model innovation, (3) Technology infrastructure, and (4) Digital transformation and capabilities. The results of this study will assist academics in identifying worldwide research trends related to the Internet of Things and Business Model Innovation as well as recommending future research areas. Full article
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16 pages, 2276 KiB  
Article
A Novel Multipath Transmission Scheme for Information-Centric Networking
by Yong Xu, Hong Ni and Xiaoyong Zhu
Future Internet 2023, 15(2), 80; https://doi.org/10.3390/fi15020080 - 17 Feb 2023
Cited by 2 | Viewed by 1304
Abstract
Due to the overload of IP semantics, the traditional TCP/IP network has a number of problems in scalability, mobility, and security. In this context, information-centric networking (ICN) is proposed to solve these problems. To reduce the cost of deployment and smoothly evolve, the [...] Read more.
Due to the overload of IP semantics, the traditional TCP/IP network has a number of problems in scalability, mobility, and security. In this context, information-centric networking (ICN) is proposed to solve these problems. To reduce the cost of deployment and smoothly evolve, the ICN architecture needs to be compatible with existing IP infrastructure. However, the rigid underlying IP routing regulation limits the data transmission efficiency of ICN. In this paper, we propose a novel multipath transmission scheme by utilizing the characteristics and functions of ICN to enhance data transmission. The process of multipath transmission can be regarded as a service, and a multipath transmission service ID (MPSID) is assigned. By using the ICN routers bound to the MPSID as relay nodes, multiple parallel paths between the data source and the receiver are constructed. Moreover, we design a path management mechanism, including path selection and path switching. It can determine the initial path based on historical transmission information and switch to other optimal paths according to the congestion degree during transmission. The experimental results show that our proposed method can improve the average throughput and reduce the average flow completion time and the average chunk completion time. Full article
(This article belongs to the Special Issue Recent Advances in Information-Centric Networks (ICNs))
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27 pages, 1093 KiB  
Article
On the Use of Knowledge Transfer Techniques for Biomedical Named Entity Recognition
by Tahir Mehmood, Ivan Serina, Alberto Lavelli, Luca Putelli and Alfonso Gerevini
Future Internet 2023, 15(2), 79; https://doi.org/10.3390/fi15020079 - 17 Feb 2023
Cited by 1 | Viewed by 1433
Abstract
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, e.g., relation extraction and semantic search. Extracting the text of interest from biomedical documents becomes more demanding as the availability of online data is increasing. Deep learning models have been [...] Read more.
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, e.g., relation extraction and semantic search. Extracting the text of interest from biomedical documents becomes more demanding as the availability of online data is increasing. Deep learning models have been adopted for biomedical named entity recognition (BioNER) as deep learning has been found very successful in many other tasks. Nevertheless, the complex structure of biomedical text data is still a challenging aspect for deep learning models. Limited annotated biomedical text data make it more difficult to train deep learning models with millions of trainable parameters. The single-task model, which focuses on learning a specific task, has issues in learning complex feature representations from a limited quantity of annotated data. Moreover, manually constructing annotated data is a time-consuming job. It is, therefore, vital to exploit other efficient ways to train deep learning models on the available annotated data. This work enhances the performance of the BioNER task by taking advantage of various knowledge transfer techniques: multitask learning and transfer learning. This work presents two multitask models (MTMs), which learn shared features and task-specific features by implementing the shared and task-specific layers. In addition, the presented trained MTM is also fine-tuned for each specific dataset to tailor it from a general features representation to a specialized features representation. The presented empirical results and statistical analysis from this work illustrate that the proposed techniques enhance significantly the performance of the corresponding single-task model (STM). Full article
(This article belongs to the Special Issue Machine Learning for Mobile Networks)
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3 pages, 171 KiB  
Editorial
Cognitive Software Defined Networking and Network Function Virtualization and Applications
by Sachin Sharma and Avishek Nag
Future Internet 2023, 15(2), 78; https://doi.org/10.3390/fi15020078 - 17 Feb 2023
Viewed by 1322
Abstract
The emergence of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has revolutionized the Internet. Using SDN, network devices can be controlled from a centralized, programmable control plane that is decoupled from their data plane, whereas with NFV, network functions (such as network [...] Read more.
The emergence of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has revolutionized the Internet. Using SDN, network devices can be controlled from a centralized, programmable control plane that is decoupled from their data plane, whereas with NFV, network functions (such as network address translation, firewall, and intrusion detection) can be virtualized instead of being implemented on proprietary hardware. In addition, Artificial Intelligence (AI) and Machine Learning (ML) techniques will be key to automating network operations and enhancing customer service. Many of the challenges behind SDN and NFV are currently being investigated in several projects all over the world using AI and ML techniques, such as AI- and software-based networking, autonomic networking, and policy-based network management. Contributions to this Special Issue come from the above areas of research. Following a rigorous review process, four excellent articles were accepted that address and go beyond many of the challenges mentioned above. Full article
31 pages, 3031 KiB  
Article
An Interactive Method for Detection of Process Activity Executions from IoT Data
by Ronny Seiger, Marco Franceschetti and Barbara Weber
Future Internet 2023, 15(2), 77; https://doi.org/10.3390/fi15020077 - 16 Feb 2023
Cited by 9 | Viewed by 1871
Abstract
The increasing number of IoT devices equipped with sensors and actuators pervading every domain of everyday life allows for improved automated monitoring and analysis of processes executed in IoT-enabled environments. While sophisticated analysis methods exist to detect specific types of activities from low-level [...] Read more.
The increasing number of IoT devices equipped with sensors and actuators pervading every domain of everyday life allows for improved automated monitoring and analysis of processes executed in IoT-enabled environments. While sophisticated analysis methods exist to detect specific types of activities from low-level IoT data, a general approach for detecting activity executions that are part of more complex business processes does not exist. Moreover, dedicated information systems to orchestrate or monitor process executions are not available in typical IoT environments. As a consequence, the large corpus of existing process analysis and mining techniques to check and improve process executions cannot be applied. In this work, we develop an interactive method guiding the analysis of low-level IoT data with the goal of detecting higher-level process activity executions. The method is derived following the exploratory data analysis of an IoT data set from a smart factory. We propose analysis steps, sensor-actuator-activity patterns, and the novel concept of activity signatures that are applicable in many IoT domains. The method shows to be valuable for the early stages of IoT data analyses to build a ground truth based on domain knowledge and decisions of the process analyst, which can be used for automated activity detection in later stages. Full article
(This article belongs to the Special Issue IoT-Based BPM for Smart Environments)
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24 pages, 1019 KiB  
Article
Effective and Efficient DDoS Attack Detection Using Deep Learning Algorithm, Multi-Layer Perceptron
by Sheeraz Ahmed, Zahoor Ali Khan, Syed Muhammad Mohsin, Shahid Latif, Sheraz Aslam, Hana Mujlid, Muhammad Adil and Zeeshan Najam
Future Internet 2023, 15(2), 76; https://doi.org/10.3390/fi15020076 - 15 Feb 2023
Cited by 11 | Viewed by 4499
Abstract
Distributed denial of service (DDoS) attacks pose an increasing threat to businesses and government agencies. They harm internet businesses, limit access to information and services, and damage corporate brands. Attackers use application layer DDoS attacks that are not easily detectable because of impersonating [...] Read more.
Distributed denial of service (DDoS) attacks pose an increasing threat to businesses and government agencies. They harm internet businesses, limit access to information and services, and damage corporate brands. Attackers use application layer DDoS attacks that are not easily detectable because of impersonating authentic users. In this study, we address novel application layer DDoS attacks by analyzing the characteristics of incoming packets, including the size of HTTP frame packets, the number of Internet Protocol (IP) addresses sent, constant mappings of ports, and the number of IP addresses using proxy IP. We analyzed client behavior in public attacks using standard datasets, the CTU-13 dataset, real weblogs (dataset) from our organization, and experimentally created datasets from DDoS attack tools: Slow Lairs, Hulk, Golden Eyes, and Xerex. A multilayer perceptron (MLP), a deep learning algorithm, is used to evaluate the effectiveness of metrics-based attack detection. Simulation results show that the proposed MLP classification algorithm has an efficiency of 98.99% in detecting DDoS attacks. The performance of our proposed technique provided the lowest value of false positives of 2.11% compared to conventional classifiers, i.e., Naïve Bayes, Decision Stump, Logistic Model Tree, Naïve Bayes Updateable, Naïve Bayes Multinomial Text, AdaBoostM1, Attribute Selected Classifier, Iterative Classifier, and OneR. Full article
(This article belongs to the Special Issue Cyber Security Challenges in the New Smart Worlds)
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27 pages, 2756 KiB  
Article
An Efficient Model-Based Clustering via Joint Multiple Sink Placement for WSNs
by Soukaina Bouarourou, Abderrahim Zannou, El Habib Nfaoui and Abdelhak Boulaalam
Future Internet 2023, 15(2), 75; https://doi.org/10.3390/fi15020075 - 15 Feb 2023
Cited by 7 | Viewed by 1942
Abstract
Wireless sensor networks consist of many restrictive sensor nodes with limited abilities, including limited power, low bandwidth and battery, small storage space, and limited computational capacity. Sensor nodes produce massive amounts of data that are then collected and transferred to the sink via [...] Read more.
Wireless sensor networks consist of many restrictive sensor nodes with limited abilities, including limited power, low bandwidth and battery, small storage space, and limited computational capacity. Sensor nodes produce massive amounts of data that are then collected and transferred to the sink via single or multihop pathways. Since the nodes’ abilities are limited, ineffective data transmission across the nodes makes the network unstable due to the rising data transmission delay and the high consumption of energy. Furthermore, sink location and sensor-to-sink routing significantly impact network performance. Although there are suggested solutions for this challenge, they suffer from low-lifetime networks, high energy consumption, and data transmission delay. Based on these constrained capacities, clustering is a promising technique for reducing the energy use of wireless sensor networks, thus improving their performance. This paper models the problem of multiple sink deployment and sensor-to-sink routing using the clustering technique to extend the lifetime of wireless sensor networks. The proposed model determines the sink placements and the most effective way to transmit data from sensor nodes to the sink. First, we propose an improved ant clustering algorithm to group nodes, and we select the cluster head based on the chance of picking factor. Second, we assign nodes to sinks that are designated as data collectors. Third, we provide optimal paths for nodes to relay the data to the sink by maximizing the network’s lifetime and improving data flow. The results of simulation on a real network dataset demonstrate that our proposal outperforms the existing state-of-the-art approaches in terms of energy consumption, network lifetime, data transmission delay, and scalability. Full article
(This article belongs to the Section Internet of Things)
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17 pages, 1026 KiB  
Article
Collaborative Storage and Resolution Method between Layers in Hierarchical ICN Name Resolution Systems
by Yanxia Li and Yang Li
Future Internet 2023, 15(2), 74; https://doi.org/10.3390/fi15020074 - 13 Feb 2023
Viewed by 903
Abstract
Name resolution system is an important infrastructure in Information Centric Networking (ICN) network architecture of identifier–locator separation mode. In the Local Name Resolution System (LNMRS), a hierarchical name resolution system for latency-sensitive scenarios; higher-level resolution nodes serve more users and suffer more storage [...] Read more.
Name resolution system is an important infrastructure in Information Centric Networking (ICN) network architecture of identifier–locator separation mode. In the Local Name Resolution System (LNMRS), a hierarchical name resolution system for latency-sensitive scenarios; higher-level resolution nodes serve more users and suffer more storage pressure, which causes the problem of unbalanced storage load between layers, and requires inter-layer collaborative storage under the constraint of deterministic service latency characteristics. In this paper, we use the constraints required for inter-layer collaborative resolution to construct an index neighbor structure and perform collaborative storage based on this structure. This method relieves storage pressure on high-level resolution nodes. Experimental results show that the increase of total storage load brought by the proposed method is 57.1% of that by MGreedy algorithm, 8.1% of that by Greedy algorithm, and 0.8% of that by the K-Mediod algorithm when relieving the same storage load for high-level resolution nodes. Meanwhile, deterministic service latency feature is still sustained when our proposed method is used for collaborative resolution. Full article
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20 pages, 656 KiB  
Article
I4.0I: A New Way to Rank How Involved a Company Is in the Industry 4.0 Era
by Vitória Francesca Biasibetti Zilli, Cesar David Paredes Crovato, Rodrigo da Rosa Righi, Rodrigo Ivan Goytia Mejia, Giovani Pesenti and Dhananjay Singh
Future Internet 2023, 15(2), 73; https://doi.org/10.3390/fi15020073 - 13 Feb 2023
Cited by 3 | Viewed by 1250
Abstract
Cloud, IoT, big data, and artificial intelligence are currently very present in the industrial and academic areas, being drivers of technological revolution. Such concepts are closely related to Industry 4.0, which can be defined as the idea of a flexible, technological, and connected [...] Read more.
Cloud, IoT, big data, and artificial intelligence are currently very present in the industrial and academic areas, being drivers of technological revolution. Such concepts are closely related to Industry 4.0, which can be defined as the idea of a flexible, technological, and connected factory, encompassing the shop floor itself and its relationship between workers, the chain of supply, and final products. Some studies have already been developed to quantify a company’s level of maturity within the scope of Industry 4.0. However, there is a lack of a global and unique index that, by receiving as input how many implemented technologies a company has, enables its classification and therefore, comparison with other companies of the same genre. Thus, we present the I4.0I (Industry 4.0 Index), an index that allows companies to measure how far they are in Industry 4.0, enabling competitiveness between factories and stimulating economic and technological growth. To assess the method, companies in the technology sector received and answered a questionnaire in which they marked the technologies they used over the years and the income obtained. The results were used to compare the I4.0I with the profit measured in the same period, proving that the greater the use of technology, the greater the benefits for the company. Full article
(This article belongs to the Special Issue Big Data Analytics for the Industrial Internet of Things)
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15 pages, 4196 KiB  
Article
Perception of the Use of Virtual Reality Didactic Tools among Faculty in Mexico
by Álvaro Antón-Sancho, Pablo Fernández-Arias and Diego Vergara
Future Internet 2023, 15(2), 72; https://doi.org/10.3390/fi15020072 - 12 Feb 2023
Cited by 1 | Viewed by 1541
Abstract
This paper develops descriptive quantitative research of the assessments of virtual reality (VR) technology, used as a didactic tool, by a sample of 712 university professors in Mexico. For this purpose, a validated Likert-type questionnaire was used as an instrument, the responses to [...] Read more.
This paper develops descriptive quantitative research of the assessments of virtual reality (VR) technology, used as a didactic tool, by a sample of 712 university professors in Mexico. For this purpose, a validated Likert-type questionnaire was used as an instrument, the responses to which were statistically analyzed. The results obtained show that professors in Mexico report low levels of digital skills, but high valuations of VR. These ratings depend strongly on the professors’ area of knowledge. In this sense, the biggest gap is between Engineering professors, who value VR better, and Humanities professors, who value it worse. There are also gender gaps and gaps due to the digital generation of the participants in the assessments made, whose behavior is also different according to the area of knowledge. As a result, some recommendations are provided to try to reduce the gaps found. Full article
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49 pages, 4508 KiB  
Article
Data Is the New Oil–Sort of: A View on Why This Comparison Is Misleading and Its Implications for Modern Data Administration
by Christoph Stach
Future Internet 2023, 15(2), 71; https://doi.org/10.3390/fi15020071 - 12 Feb 2023
Cited by 4 | Viewed by 3479
Abstract
Currently, data are often referred to as the oil of the 21st century. This comparison is not only used to express that the resource data are just as important for the fourth industrial revolution as oil was for the technological revolution in the [...] Read more.
Currently, data are often referred to as the oil of the 21st century. This comparison is not only used to express that the resource data are just as important for the fourth industrial revolution as oil was for the technological revolution in the late 19th century. There are also further similarities between these two valuable resources in terms of their handling. Both must first be discovered and extracted from their sources. Then, the raw materials must be cleaned, preprocessed, and stored before they can finally be delivered to consumers. Despite these undeniable similarities, however, there are significant differences between oil and data in all of these processing steps, making data a resource that is considerably more challenging to handle. For instance, data sources, as well as the data themselves, are heterogeneous, which means there is no one-size-fits-all data acquisition solution. Furthermore, data can be distorted by the source or by third parties without being noticed, which affects both quality and usability. Unlike oil, there is also no uniform refinement process for data, as data preparation should be tailored to the subsequent consumers and their intended use cases. With regard to storage, it has to be taken into account that data are not consumed when they are processed or delivered to consumers, which means that the data volume that has to be managed is constantly growing. Finally, data may be subject to special constraints in terms of distribution, which may entail individual delivery plans depending on the customer and their intended purposes. Overall, it can be concluded that innovative approaches are needed for handling the resource data that address these inherent challenges. In this paper, we therefore study and discuss the relevant characteristics of data making them such a challenging resource to handle. In order to enable appropriate data provisioning, we introduce a holistic research concept from data source to data sink that respects the processing requirements of data producers as well as the quality requirements of data consumers and, moreover, ensures a trustworthy data administration. Full article
(This article belongs to the Special Issue Security and Privacy in Blockchains and the IoT II)
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21 pages, 12914 KiB  
Article
Im2Graph: A Weakly Supervised Approach for Generating Holistic Scene Graphs from Regional Dependencies
by Swarnendu Ghosh, Teresa Gonçalves and Nibaran Das
Future Internet 2023, 15(2), 70; https://doi.org/10.3390/fi15020070 - 10 Feb 2023
Viewed by 1423
Abstract
Conceptual representations of images involving descriptions of entities and their relations are often represented using scene graphs. Such scene graphs can express relational concepts by using sets of triplets [...] Read more.
Conceptual representations of images involving descriptions of entities and their relations are often represented using scene graphs. Such scene graphs can express relational concepts by using sets of triplets subjectpredicateobject. Instead of building dedicated models for scene graph generation, our model tends to extract the latent relational information implicitly encoded in image captioning models. We explored dependency parsing to build grammatically sound parse trees from captions. We used detection algorithms for the region propositions to generate dense region-based concept graphs. These were optimally combined using the approximate sub-graph isomorphism to create holistic concept graphs for images. The major advantages of this approach are threefold. Firstly, the proposed graph generation module is completely rule-based and, hence, adheres to the principles of explainable artificial intelligence. Secondly, graph generation can be used as plug-and-play along with any region proposition and caption generation framework. Finally, our results showed that we could generate rich concept graphs without explicit graph-based supervision. Full article
(This article belongs to the Special Issue Deep Learning and Natural Language Processing)
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16 pages, 4653 KiB  
Article
Designing for the Metaverse: A Multidisciplinary Laboratory in the Industrial Design Program
by Marina Ricci, Alessandra Scarcelli and Michele Fiorentino
Future Internet 2023, 15(2), 69; https://doi.org/10.3390/fi15020069 - 10 Feb 2023
Cited by 6 | Viewed by 3230
Abstract
The design research and education landscapes are changing. The widespread development and use of technologies such as Mixed Reality (MR) and the diffusion of Head-Mounted Displays (HMDs) available at low cost are causing a shift in design education toward the Metaverse. In this [...] Read more.
The design research and education landscapes are changing. The widespread development and use of technologies such as Mixed Reality (MR) and the diffusion of Head-Mounted Displays (HMDs) available at low cost are causing a shift in design education toward the Metaverse. In this ever-changing scenario, there is a need to rethink design and teaching methods. However, scientific literature lacks the ability to provide contributions that include MR technology education in the industrial design program. We, therefore, present an innovative laboratory with an integrated multidisciplinary approach that starts from the fundamentals of interaction design and aims to teach students how to design next-generation MR interfaces for the Metaverse. The lab combines theory and practice within three courses: Information Design, Information Systems, and Virtual Design and Simulation. Industrial design students follow a precise multidisciplinary method consisting of five steps, from state-of-the-art analysis to the presentation of a final group design of an MR user interface. Thus, we introduce a class case study by presenting the outcomes of a semester project in the field of household appliances. Evaluation of the teaching method is conducted through a semi-structured questionnaire. Preliminary results show positive outcomes from students in terms of acceptance, effectiveness, usefulness, efficiency, and satisfaction with the teaching method adopted for the laboratory. Full article
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20 pages, 13851 KiB  
Article
RingFFL: A Ring-Architecture-Based Fair Federated Learning Framework
by Lu Han, Xiaohong Huang, Dandan Li and Yong Zhang
Future Internet 2023, 15(2), 68; https://doi.org/10.3390/fi15020068 - 09 Feb 2023
Viewed by 1331
Abstract
In the ring-architecture-based federated learning framework, security and fairness are severely compromised when dishonest clients abort the training process after obtaining useful information. To solve the problem, we propose a Ring- architecture-based Fair Federated Learning framework called RingFFL, in which [...] Read more.
In the ring-architecture-based federated learning framework, security and fairness are severely compromised when dishonest clients abort the training process after obtaining useful information. To solve the problem, we propose a Ring- architecture-based Fair Federated Learning framework called RingFFL, in which we design a penalty mechanism for FL. Before the training starts in each round, all clients that will participate in the training pay deposits in a set order and record the transactions on the blockchain to ensure that they are not tampered with. Subsequently, the clients perform the FL training process, and the correctness of the models transmitted by the clients is guaranteed by the HASH algorithm during the training process. When all clients perform honestly, each client can obtain the final model, and the number of digital currencies in each client’s wallet is kept constant; otherwise, the deposits of clients who leave halfway will be compensated to the clients who perform honestly during the training process. In this way, through the penalty mechanism, all clients either obtain the final model or are compensated, thus ensuring the fairness of federated learning. The security analysis and experimental results show that RingFFL not only guarantees the accuracy and security of the federated learning model but also guarantees the fairness. Full article
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14 pages, 1555 KiB  
Article
A Simple Model of Knowledge Scaffolding Applied to Wikipedia Growth
by Franco Bagnoli and Guido de Bonfioli Cavalcabo’
Future Internet 2023, 15(2), 67; https://doi.org/10.3390/fi15020067 - 06 Feb 2023
Cited by 1 | Viewed by 1487
Abstract
We illustrate a simple model of knowledge scaffolding, based on the process of building a corpus of knowledge, each item of which is linked to “previous” ones. The basic idea is that the relationships among the items of corpus can be essentially drawn [...] Read more.
We illustrate a simple model of knowledge scaffolding, based on the process of building a corpus of knowledge, each item of which is linked to “previous” ones. The basic idea is that the relationships among the items of corpus can be essentially drawn as an acyclic network, in which topmost contributions are “derived” from items at lower levels. When a new item is added to the corpus, we impose a limit to the maximum unit increase (i.e., “jumps”) of knowledge. We analyzed the time growth of the corpus (number of items) and the maximum knowledge, both showing a power law. Another result was that the number of “holes” in the knowledge corpus always remains limited. Our model can be used as a rough approximation to the asymptotic growth of Wikipedia, and indeed, actual data show a certain resemblance with our model. Assuming that the user base is growing, at beginning, in an exponential way, one can also recover the early phases of Wikipedia growth. Full article
(This article belongs to the Special Issue State-of-the-Art Future Internet Technology in Italy 2022–2023)
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21 pages, 771 KiB  
Review
Disruptive Technologies for Parliaments: A Literature Review
by Dimitris Koryzis, Dionisis Margaris, Costas Vassilakis, Konstantinos Kotis and Dimitris Spiliotopoulos
Future Internet 2023, 15(2), 66; https://doi.org/10.3390/fi15020066 - 05 Feb 2023
Cited by 2 | Viewed by 2066
Abstract
Exploitation and use of disruptive technologies, such as the Internet of Things, recommender systems, and artificial intelligence, with an ambidextrous balance, are a challenge, nowadays. Users of the technologies, and stakeholders, could be part of a new organisational model that affects business procedures [...] Read more.
Exploitation and use of disruptive technologies, such as the Internet of Things, recommender systems, and artificial intelligence, with an ambidextrous balance, are a challenge, nowadays. Users of the technologies, and stakeholders, could be part of a new organisational model that affects business procedures and processes. Additionally, the use of inclusive participatory organisational models is essential for the effective adoption of these technologies. Such models aim to transform organisational structures, as well. Public organisations, such as the parliament, could utilise information systems’ personalisation techniques. As there are a lot of efforts to define the framework, the methodology, the techniques, the platforms, and the suitable models for digital technologies adoption in public organisations, this paper aims to provide a literature review for disruptive technology inclusive use in parliaments. The review emphasises the assessment of the applicability of the technologies, their maturity and usefulness, user acceptance, their performance, and their correlation to the adoption of relevant innovative, inclusive organisational models. It is argued that the efficient digital transformation of democratic institutions, such as parliaments, with the use of advanced e-governance tools and disruptive technologies, requires strategic approaches for adoption, acceptance, and inclusive service adaptation. Full article
(This article belongs to the Special Issue Smart Data and Systems for the Internet of Things)
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19 pages, 7857 KiB  
Article
Multi-Scale Audio Spectrogram Transformer for Classroom Teaching Interaction Recognition
by Fan Liu and Jiandong Fang
Future Internet 2023, 15(2), 65; https://doi.org/10.3390/fi15020065 - 02 Feb 2023
Cited by 1 | Viewed by 1990
Abstract
Classroom interactivity is one of the important metrics for assessing classrooms, and identifying classroom interactivity through classroom image data is limited by the interference of complex teaching scenarios. However, audio data within the classroom are characterized by significant student–teacher interaction. This study proposes [...] Read more.
Classroom interactivity is one of the important metrics for assessing classrooms, and identifying classroom interactivity through classroom image data is limited by the interference of complex teaching scenarios. However, audio data within the classroom are characterized by significant student–teacher interaction. This study proposes a multi-scale audio spectrogram transformer (MAST) speech scene classification algorithm and constructs a classroom interactive audio dataset to achieve interactive teacher–student recognition in the classroom teaching process. First, the original speech signal is sampled and pre-processed to generate a multi-channel spectrogram, which enhances the representation of features compared with single-channel features; Second, in order to efficiently capture the long-range global context of the audio spectrogram, the audio features are globally modeled by the multi-head self-attention mechanism of MAST, and the feature resolution is reduced during feature extraction to continuously enrich the layer-level features while reducing the model complexity; Finally, a further combination with a time-frequency enrichment module maps the final output to a class feature map, enabling accurate audio category recognition. The experimental comparison of MAST is carried out on the public environment audio dataset and the self-built classroom audio interaction datasets. Compared with the previous state-of-the-art methods on public datasets AudioSet and ESC-50, its accuracy has been improved by 3% and 5%, respectively, and the accuracy of the self-built classroom audio interaction dataset has reached 92.1%. These results demonstrate the effectiveness of MAST in the field of general audio classification and the smart classroom domain. Full article
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20 pages, 1036 KiB  
Article
Significance of Cross-Correlated QoS Configurations for Validating the Subjective and Objective QoE of Cloud Gaming Applications
by Nafi Ahmad, Abdul Wahab, John Schormans and Ali Adib Arnab
Future Internet 2023, 15(2), 64; https://doi.org/10.3390/fi15020064 - 02 Feb 2023
Cited by 2 | Viewed by 1696
Abstract
In this paper, utilising real-internet traffic data, we modified a popular network emulator to better imitate real network traffic and studied its subjective and objective implications on QoE for cloud-gaming apps. Subjective QoE evaluation was then used to compare cross-correlated QoS metric with [...] Read more.
In this paper, utilising real-internet traffic data, we modified a popular network emulator to better imitate real network traffic and studied its subjective and objective implications on QoE for cloud-gaming apps. Subjective QoE evaluation was then used to compare cross-correlated QoS metric with the default non-correlated emulator setup. Human test subjects showed different correlated versus non-correlated QoS parameters affects regarding cloud gaming QoE. Game-QoE is influenced more by network degradation than video QoE. To validate our subjective QoE study, we analysed the experiment’s video objectively. We tested how well Full-Reference VQA measures subjective QoE. The correlation between FR QoE and subjective MOS was greater in non-correlated QoS than in correlated QoS conditions. We also found that correlated scenarios had more stuttering events compared to non-correlated scenarios, resulting in lower game QoE. Full article
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31 pages, 1849 KiB  
Article
Vendor-Agnostic Reconfiguration of Kubernetes Clusters in Cloud Federations
by Eddy Truyen, Hongjie Xie and Wouter Joosen
Future Internet 2023, 15(2), 63; https://doi.org/10.3390/fi15020063 - 01 Feb 2023
Cited by 1 | Viewed by 2129
Abstract
Kubernetes (K8s) defines standardized APIs for container-based cluster orchestration such that it becomes possible for application managers to deploy their applications in a portable and interopable manner. However, a practical problem arises when the same application must be replicated in a distributed fashion [...] Read more.
Kubernetes (K8s) defines standardized APIs for container-based cluster orchestration such that it becomes possible for application managers to deploy their applications in a portable and interopable manner. However, a practical problem arises when the same application must be replicated in a distributed fashion across different edge, fog and cloud sites; namely, there will not exist a single K8s vendor that is able to provision and manage K8s clusters across all these sites. Hence, the problem of feature incompatibility between different K8s vendors arises. A large number of documented features in the open-source distribution of K8s are optional features that are turned off by default but can be activated by setting specific combinations of parameters and plug-in components in configuration manifests for the K8s control plane and worker node agents. However, none of these configuration manifests are standardized, giving K8s vendors the freedom to hide the manifests behind a single, more restricted, and proprietary customization interface. Therefore, some optional K8s features cannot be activated consistently across K8s vendors and applications that require these features cannot be run on those vendors. In this paper, we present a unified, vendor-agnostic feature management approach for consistently configuring optional K8s features across a federation of clusters hosted by different Kubernetes vendors. We describe vendor-agnostic reconfiguration tactics that are already applied in industry and that cover a wide range of optional K8s features. Based on these tactics, we design and implement an autonomic controller for declarative feature compatibility management across a cluster federation. We found that the features configured through our vendor-agnostic approach have no impact on application performance when compared with a cluster where the features are configured using the configuration manifests of the open-source K8s distribution. Moreover, the maximum time to complete reconfiguration of a single feature is within 100 seconds, which is 6 times faster than using proprietary customization interfaces of mainstream K8s vendors such as Google Kubernetes Engine. However, there is a non-negligible disruption to running applications when performing the reconfiguration to an existing cluster; this disruption impact does not appear using the proprietary customization methods of the K8s vendors due to the use of rolling upgrade of cluster nodes. Therefore, our approach is best applied in the following three use cases: (i) when starting up new K8s clusters, (ii) when optional K8s features of existing clusters must be activated as quickly as possibly and temporary disruption to running applications can be tolerated or (iii) when proprietary customization interfaces do not allow to activate the desired optional feature. Full article
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34 pages, 2856 KiB  
Review
Adversarial Machine Learning Attacks against Intrusion Detection Systems: A Survey on Strategies and Defense
by Afnan Alotaibi and Murad A. Rassam
Future Internet 2023, 15(2), 62; https://doi.org/10.3390/fi15020062 - 31 Jan 2023
Cited by 15 | Viewed by 6825
Abstract
Concerns about cybersecurity and attack methods have risen in the information age. Many techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs), that help achieve security goals, such as detecting malicious attacks before they enter the system and [...] Read more.
Concerns about cybersecurity and attack methods have risen in the information age. Many techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs), that help achieve security goals, such as detecting malicious attacks before they enter the system and classifying them as malicious activities. However, the IDS approaches have shortcomings in misclassifying novel attacks or adapting to emerging environments, affecting their accuracy and increasing false alarms. To solve this problem, researchers have recommended using machine learning approaches as engines for IDSs to increase their efficacy. Machine-learning techniques are supposed to automatically detect the main distinctions between normal and malicious data, even novel attacks, with high accuracy. However, carefully designed adversarial input perturbations during the training or testing phases can significantly affect their predictions and classifications. Adversarial machine learning (AML) poses many cybersecurity threats in numerous sectors that use machine-learning-based classification systems, such as deceiving IDS to misclassify network packets. Thus, this paper presents a survey of adversarial machine-learning strategies and defenses. It starts by highlighting various types of adversarial attacks that can affect the IDS and then presents the defense strategies to decrease or eliminate the influence of these attacks. Finally, the gaps in the existing literature and future research directions are presented. Full article
(This article belongs to the Special Issue Machine Learning Integration with Cyber Security II)
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13 pages, 2344 KiB  
Article
Forest Fire Detection and Notification Method Based on AI and IoT Approaches
by Kuldoshbay Avazov, An Eui Hyun, Alabdulwahab Abrar Sami S, Azizbek Khaitov, Akmalbek Bobomirzaevich Abdusalomov and Young Im Cho
Future Internet 2023, 15(2), 61; https://doi.org/10.3390/fi15020061 - 31 Jan 2023
Cited by 19 | Viewed by 5470
Abstract
There is a high risk of bushfire in spring and autumn, when the air is dry. Do not bring any flammable substances, such as matches or cigarettes. Cooking or wood fires are permitted only in designated areas. These are some of the regulations [...] Read more.
There is a high risk of bushfire in spring and autumn, when the air is dry. Do not bring any flammable substances, such as matches or cigarettes. Cooking or wood fires are permitted only in designated areas. These are some of the regulations that are enforced when hiking or going to a vegetated forest. However, humans tend to disobey or disregard guidelines and the law. Therefore, to preemptively stop people from accidentally starting a fire, we created a technique that will allow early fire detection and classification to ensure the utmost safety of the living things in the forest. Some relevant studies on forest fire detection have been conducted in the past few years. However, there are still insufficient studies on early fire detection and notification systems for monitoring fire disasters in real time using advanced approaches. Therefore, we came up with a solution using the convergence of the Internet of Things (IoT) and You Only Look Once Version 5 (YOLOv5). The experimental results show that IoT devices were able to validate some of the falsely detected fires or undetected fires that YOLOv5 reported. This report is recorded and sent to the fire department for further verification and validation. Finally, we compared the performance of our method with those of recently reported fire detection approaches employing widely used performance matrices to test the achieved fire classification results. Full article
(This article belongs to the Special Issue Machine Learning Perspective in the Convolutional Neural Network Era)
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12 pages, 4147 KiB  
Article
Performance Assessment and Comparison of Deployment Options for 5G Millimeter Wave Systems
by Evgeni Mokrov and Konstantin Samouylov
Future Internet 2023, 15(2), 60; https://doi.org/10.3390/fi15020060 - 31 Jan 2023
Cited by 1 | Viewed by 988
Abstract
The roll-outs of fifth-generation (5G) New Radio (NR) systems operating in the millimeter-wave (mmWave) frequency band are essential for satisfying IMT-2020 requirements set forth by ITU-R in terms of the data rate at the access interface. To overcome mmWave-specific propagation phenomena, a number [...] Read more.
The roll-outs of fifth-generation (5G) New Radio (NR) systems operating in the millimeter-wave (mmWave) frequency band are essential for satisfying IMT-2020 requirements set forth by ITU-R in terms of the data rate at the access interface. To overcome mmWave-specific propagation phenomena, a number of radio access network densification options have been proposed, including a conventional base station (BS) as well as integrated access and backhaul (IAB) with terrestrial and aerial IAB nodes. The aim of this paper is to qualitatively and quantitatively compare the proposed deployments using coverage, spectral efficiency and BS density as the main metrics of interest. To this end, we develop a model capturing the specifics of various deployment options. Our numerical results demonstrate that, while the implementation of terrestrial relaying nodes potentially improves coverage and spectral efficiency, aerial relays provide the highest coverage, three times that of a direct link connection, and also significantly reduce the required BS density. The main benefit is provided by the link between the BS and the aerial relay. However, gains are highly dependent on a number of elements in antenna arrays and targeted outage probability. The use of terrestrial relays can be considered a natural trade-off between coverage and the aggregate rate. Full article
(This article belongs to the Special Issue Performance and QoS Issues of 5G Wireless Networks and Beyond)
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32 pages, 2154 KiB  
Article
From Service Composition to Mashup Editor: A Multiperspective Taxonomy
by Abderrahmane Maaradji, Hakim Hacid and Assia Soukane
Future Internet 2023, 15(2), 59; https://doi.org/10.3390/fi15020059 - 31 Jan 2023
Viewed by 1443
Abstract
Service-oriented computing has become a popular area of research, with a particular focus on service composition. There have been many developments in this field, such as new techniques for data engineering in service description languages, protocols for publication and discovery, the optimization of [...] Read more.
Service-oriented computing has become a popular area of research, with a particular focus on service composition. There have been many developments in this field, such as new techniques for data engineering in service description languages, protocols for publication and discovery, the optimization of service selection and scheduling, and the deployment and monitoring of composed services. However, this diversity of approaches and methodologies can make it challenging to navigate between different proposed solutions and identify research gaps. In order to provide a clearer understanding of this body of work, this paper presents a comprehensive framework for the taxonomy of service composition approaches, methodologies, and tools. This framework proposes a structured view of different perspectives, such as formal, semantic, and automatic approaches, with a particular focus on the end-user’s perspective and tools such as Mashups. Full article
(This article belongs to the Special Issue Semantic Web Services for Multi-Agent Systems)
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21 pages, 4165 KiB  
Article
An Optimized Planning Tool for Microwave Terrestrial and Satellite Link Design
by Eduardo Ferreira, Pedro Sebastião, Francisco Cercas, Carlos Sá Costa and Américo Correia
Future Internet 2023, 15(2), 58; https://doi.org/10.3390/fi15020058 - 31 Jan 2023
Viewed by 1382
Abstract
Today, the internet is fundamental to social inclusion. There are many people that live in remote areas, and the only way to supply internet services is through the use of microwave terrestrial and satellite systems. Thus, it is important to have efficient tools [...] Read more.
Today, the internet is fundamental to social inclusion. There are many people that live in remote areas, and the only way to supply internet services is through the use of microwave terrestrial and satellite systems. Thus, it is important to have efficient tools to design and optimize these systems. In this paper, a tool with the objective to shorten the time spent in the design process of microwave terrestrial and satellite point-to-point links is presented. This tool can be applied in academia by engineering students, providing an extended analysis of many sections of a link project design, as well as in professional practice by telecommunication engineering departments, presenting a concise step-by-step interactive design process. This tool uses three-dimensional world visualization, with the Cesium Application Programming Interface (API), to display and analyze site-specific characteristics that can disrupt the link’s quality of service (QoS). Using this visualization, two ray-tracing algorithms were developed to analyze signal diffraction and reflection mainly throughout terrestrial links. Using this new algorithm, an innovative process for signal diffraction and reflection calculations was created. Using updated standards provided by the International Telecommunication Union Radiocommunication Sector (ITU-R), the characteristics of the defined simulated links could be predicted, thus providing the user with the metrics of signal quality and system link budget. Full article
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10 pages, 1190 KiB  
Article
Vision, Enabling Technologies, and Scenarios for a 6G-Enabled Internet of Verticals (6G-IoV)
by Maziar Nekovee and Ferheen Ayaz
Future Internet 2023, 15(2), 57; https://doi.org/10.3390/fi15020057 - 30 Jan 2023
Cited by 2 | Viewed by 1823
Abstract
5G is the critical mobile infrastructure required to both enable and accelerate the full digital transformation of vertical sectors. While the 5G for vertical sectors is aiming at connectivity requirements of specific verticals, such as manufacturing, automotive and energy, we envisage that in [...] Read more.
5G is the critical mobile infrastructure required to both enable and accelerate the full digital transformation of vertical sectors. While the 5G for vertical sectors is aiming at connectivity requirements of specific verticals, such as manufacturing, automotive and energy, we envisage that in the longer term the expansion of wide area cellular connectivity to these sectors will pave the way for a transformation to a new Internet of Verticals (IoV) in the 6G era, which we call 6G-IoV. In this paper, we describe our vision of 6G-IoV and examine its emerging and future architectural and networking enablers. We then illustrate our vision by describing a number of future scenarios of the 6G-IoV, namely the Internet of Cloud Manufacturing accounting for around 25% of digital services and products, the Internet of Robotics to cater the challenges of the growing number of robotics and expected 7% increase in usage over the coming years and the Internet of Smart Energy Grids for net-zero energy balance and shifting to 100% dependence on the renewables of energy generation. Full article
(This article belongs to the Special Issue Moving towards 6G Wireless Technologies)
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16 pages, 1468 KiB  
Article
The Energy Efficiency of Heterogeneous Cellular Networks Based on the Poisson Hole Process
by Yonghong Chen, Lei Xun and Shibing Zhang
Future Internet 2023, 15(2), 56; https://doi.org/10.3390/fi15020056 - 30 Jan 2023
Cited by 3 | Viewed by 983
Abstract
In order to decrease energy consumption caused by the dense deployment of pico base stations (PBSs) in heterogeneous cellular networks (HetNets), this paper first analyzes the energy efficiency (EE) of two-tier HetNets and then proposes a method to maximize the network EE by [...] Read more.
In order to decrease energy consumption caused by the dense deployment of pico base stations (PBSs) in heterogeneous cellular networks (HetNets), this paper first analyzes the energy efficiency (EE) of two-tier HetNets and then proposes a method to maximize the network EE by adjusting the PBS transmit power. The two-tier HetNets are modeled by the Poisson point process (PPP) and the Poisson hole process (PHP), and then the coverage probability of the macro base station (MBS) and the PBS in the two-tier HetNets is derived based on the mean interference to signal ratio (MISR). According to the user association probability, the coverage probability of the PPP-PHP HetNets is obtained. Then, the tractable expression of the average achievable rate is deduced on the basis of the relationship between the coverage probability and the average achievable rate. Finally, the expression of EE is derived and the EE optimization algorithm is proposed based on the PBS transmit power. The simulation results show that the PPP-PHP network is superior to the PPP-PPP network in terms of coverage probability and EE, and the network EE can be effectively improved by setting an appropriate PBS transmit power. Full article
(This article belongs to the Special Issue 5G Wireless Communication Networks)
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