Journal Description
Future Internet
Future Internet
is a scholarly, peer-reviewed, open access journal on Internet technologies and the information society, published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), Ei Compendex, dblp, Inspec, and many other databases.
- Journal Rank: CiteScore - Q2 (Computer Networks and Communications)
- Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 10.7 days after submission; acceptance to publication is undertaken in 3.5 days (median values for papers published in this journal in the first half of 2021).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Latest Articles
Stiffness Analysis to Predict the Spread Out of Fake Information
Future Internet 2021, 13(9), 222; https://doi.org/10.3390/fi13090222 - 28 Aug 2021
Abstract
This work highlights how the stiffness index, which is often used as a measure of stiffness for differential problems, can be employed to model the spread of fake news. In particular, we show that the higher the stiffness index is, the more rapid
[...] Read more.
This work highlights how the stiffness index, which is often used as a measure of stiffness for differential problems, can be employed to model the spread of fake news. In particular, we show that the higher the stiffness index is, the more rapid the transit of fake news in a given population. The illustration of our idea is presented through the stiffness analysis of the classical SIR model, commonly used to model the spread of epidemics in a given population. Numerical experiments, performed on real data, support the effectiveness of the approach.
Full article
(This article belongs to the Section Internet of Things)
Open AccessArticle
A BIM-Based Smart System for Fire Evacuation
by
and
Future Internet 2021, 13(9), 221; https://doi.org/10.3390/fi13090221 - 25 Aug 2021
Abstract
Building fires constitute a significant threat that affects property, the environment, and human health. The management of this risk requires an efficient fire evacuation system for buildings’ occupants. Therefore, a smart fire evacuation system that combines building information modeling (BIM) and smart technologies
[...] Read more.
Building fires constitute a significant threat that affects property, the environment, and human health. The management of this risk requires an efficient fire evacuation system for buildings’ occupants. Therefore, a smart fire evacuation system that combines building information modeling (BIM) and smart technologies is proposed. The system provides the following capacities: (i) early fire detection; (ii) the evaluation of environmental data; (iii) the identification of the best evacuation path; and (iv) information for occupants about the best evacuation routes. The system was implemented in a research building at Lille University in France. The results show the system’s capacities and benefits, particularly for the identification of the best evacuation paths.
Full article
(This article belongs to the Collection Innovative People-Centered Solutions Applied to Industries)
►▼
Show Figures

Figure 1
Open AccessArticle
Trend Prediction of Event Popularity from Microblogs
by
and
Future Internet 2021, 13(9), 220; https://doi.org/10.3390/fi13090220 - 24 Aug 2021
Abstract
Owing to rapid development of the Internet and the rise of the big data era, microblog has become the main means for people to spread and obtain information. If people can accurately predict the development trend of a microblog event, it will be
[...] Read more.
Owing to rapid development of the Internet and the rise of the big data era, microblog has become the main means for people to spread and obtain information. If people can accurately predict the development trend of a microblog event, it will be of great significance for the government to carry out public relations activities on network event supervision and guide the development of microblog event reasonably for network crisis. This paper presents effective solutions to deal with trend prediction of microblog events’ popularity. Firstly, by selecting the influence factors and quantifying the weight of each factor with an information entropy algorithm, the microblog event popularity is modeled. Secondly, the singular spectrum analysis is carried out to decompose and reconstruct the time series of the popularity of microblog event. Then, the box chart method is used to divide the popularity of microblog event into various trend spaces. In addition, this paper exploits the Bi-LSTM model to deal with trend prediction with a sequence to label model. Finally, the comparative experimental analysis is carried out on two real data sets crawled from Sina Weibo platform. Compared to three comparative methods, the experimental results show that our proposal improves F1-score by up to 39%.
Full article
(This article belongs to the Section Big Data and Augmented Intelligence)
Open AccessArticle
Spiking Neural Network-Based Near-Sensor Computing for Damage Detection in Structural Health Monitoring
by
, , , , , and
Future Internet 2021, 13(8), 219; https://doi.org/10.3390/fi13080219 - 23 Aug 2021
Abstract
In this work, we present an innovative approach for damage detection of infrastructures on-edge devices, exploiting a brain-inspired algorithm. The proposed solution exploits recurrent spiking neural networks (LSNNs), which are emerging for their theoretical energy efficiency and compactness, to recognise damage conditions by
[...] Read more.
In this work, we present an innovative approach for damage detection of infrastructures on-edge devices, exploiting a brain-inspired algorithm. The proposed solution exploits recurrent spiking neural networks (LSNNs), which are emerging for their theoretical energy efficiency and compactness, to recognise damage conditions by processing data from low-cost accelerometers (MEMS) directly on the sensor node. We focus on designing an efficient coding of MEMS data to optimise SNN execution on a low-power microcontroller. We characterised and profiled LSNN performance and energy consumption on a hardware prototype sensor node equipped with an STM32 embedded microcontroller and a digital MEMS accelerometer. We used a hardware-in-the-loop environment with virtual sensors generating data on an SPI interface connected to the physical microcontroller to evaluate the system with a data stream from a real viaduct. We exploited this environment also to study the impact of different on-sensor encoding techniques, mimicking a bio-inspired sensor able to generate events instead of accelerations. Obtained results show that the proposed optimised embedded LSNN (eLSNN), when using a spike-based input encoding technique, achieves 54% lower execution time with respect to a naive LSNN algorithm implementation present in the state-of-the-art. The optimised eLSNN requires around 47 kCycles, which is comparable with the data transfer cost from the SPI interface. However, the spike-based encoding technique requires considerably larger input vectors to get the same classification accuracy, resulting in a longer pre-processing and sensor access time. Overall the event-based encoding techniques leads to a longer execution time (1.49×) but similar energy consumption. Moving this coding on the sensor can remove this limitation leading to an overall more energy-efficient monitoring system.
Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
►▼
Show Figures

Figure 1
Open AccessReview
IoT for Smart Cities: Machine Learning Approaches in Smart Healthcare—A Review
by
, , , , , , and
Future Internet 2021, 13(8), 218; https://doi.org/10.3390/fi13080218 - 23 Aug 2021
Abstract
Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in
[...] Read more.
Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in politics, business, administration and urban planning since the 2000s to establish tech-based changes and innovations in urban areas. The idea of the smart city is used in conjunction with the utilization of digital technologies and at the same time represents a reaction to the economic, social and political challenges that post-industrial societies are confronted with at the start of the new millennium. The key focus is on dealing with challenges faced by urban society, such as environmental pollution, demographic change, population growth, healthcare, the financial crisis or scarcity of resources. In a broader sense, the term also includes non-technical innovations that make urban life more sustainable. So far, the idea of using IoT-based sensor networks for healthcare applications is a promising one with the potential of minimizing inefficiencies in the existing infrastructure. A machine learning approach is key to successful implementation of the IoT-powered wireless sensor networks for this purpose since there is large amount of data to be handled intelligently. Throughout this paper, it will be discussed in detail how AI-powered IoT and WSNs are applied in the healthcare sector. This research will be a baseline study for understanding the role of the IoT in smart cities, in particular in the healthcare sector, for future research works.
Full article
(This article belongs to the Special Issue AI and IoT technologies in Smart Cities)
►▼
Show Figures

Figure 1
Open AccessArticle
A Data Sharing Scheme for GDPR-Compliance Based on Consortium Blockchain
Future Internet 2021, 13(8), 217; https://doi.org/10.3390/fi13080217 - 21 Aug 2021
Abstract
After the General Data Protection Regulation (GDPR) was introduced, some organizations and big data companies shared data without conducting any privacy protection and compliance authentication, which endangered user data security, and were punished financially for this reason. This study proposes a blockchain-based GDPR
[...] Read more.
After the General Data Protection Regulation (GDPR) was introduced, some organizations and big data companies shared data without conducting any privacy protection and compliance authentication, which endangered user data security, and were punished financially for this reason. This study proposes a blockchain-based GDPR compliance data sharing scheme, aiming to promote compliance with regulations and provide a tool for interaction between users and service providers to achieve data security sharing. The zero-knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARK) algorithm is adopted for protecting data and ensure that the user’s private data can satisfy the individual requirements of the service provider without exposing user data. The proposed scheme ensures mutual authentication through the Proof of Authority consensus based on the Committee Endorsement Mechanism (CEM-PoA), and prevents nodes from doing evil using the reputation incentive mechanism. Theoretical analysis and performance comparison indicate that the scheme meets the confidentiality, availability, and other indicators. It has superiority in efficiency and privacy protection compared with other schemes.
Full article
(This article belongs to the Special Issue Big Data Security and Privacy: Opportunities, Challenges and Solutions)
►▼
Show Figures

Figure 1
Open AccessArticle
Cross-Project Defect Prediction Method Based on Manifold Feature Transformation
Future Internet 2021, 13(8), 216; https://doi.org/10.3390/fi13080216 - 20 Aug 2021
Abstract
Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data. However, in the practical realm of software development, the
[...] Read more.
Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data. However, in the practical realm of software development, the software project that needs to be predicted is generally a brand new software project, and there is not enough labeled data to build a defect prediction model; therefore, traditional methods are no longer applicable. Cross-project defect prediction uses the labeled data of the same type of project similar to the target project to build the defect prediction model, so as to solve the problem of data loss in traditional methods. However, the difference in data distribution between the same type of project and the target project reduces the performance of defect prediction. To solve this problem, this paper proposes a cross-project defect prediction method based on manifold feature transformation. This method transforms the original feature space of the project into a manifold space, then reduces the difference in data distribution of the transformed source project and the transformed target project in the manifold space, and finally uses the transformed source project to train a naive Bayes prediction model with better performance. A comparative experiment was carried out using the Relink dataset and the AEEEM dataset. The experimental results show that compared with the benchmark method and several cross-project defect prediction methods, the proposed method effectively reduces the difference in data distribution between the source project and the target project, and obtains a higher F1 value, which is an indicator commonly used to measure the performance of the two-class model.
Full article
(This article belongs to the Section Big Data and Augmented Intelligence)
►▼
Show Figures

Figure 1
Open AccessArticle
Two-Layer Reversible Data Hiding for VQ-Compressed Images Based on De-Clustering and Indicator-Free Search-Order Coding
Future Internet 2021, 13(8), 215; https://doi.org/10.3390/fi13080215 - 20 Aug 2021
Abstract
During transmission of digital images, secret messages can be embedded using data hiding techniques. Such techniques can transfer private secrets without drawing the attention of eavesdroppers. To reduce the amount of transmitted data, image compression methods are widely applied. Hiding secret data in
[...] Read more.
During transmission of digital images, secret messages can be embedded using data hiding techniques. Such techniques can transfer private secrets without drawing the attention of eavesdroppers. To reduce the amount of transmitted data, image compression methods are widely applied. Hiding secret data in compressed images is a hot issue recently. In this paper, we apply the de-clustering concept and the indicator-free search-order coding (IFSOC) technique to hide information into vector quantization (VQ) compressed images. Experimental results show that the proposed two-layer reversible data hiding scheme for IFSOC-encoded VQ index table can hide a large amount of secret data among state-of-the-art methods with a relatively lower bit rate and high security.
Full article
(This article belongs to the Special Issue Research and Application of Information Hiding and Cryptography)
►▼
Show Figures

Figure 1
Open AccessArticle
Intraoperative Use of Mixed Reality Technology in Median Neck and Branchial Cyst Excision
by
, , , , , , , and
Future Internet 2021, 13(8), 214; https://doi.org/10.3390/fi13080214 - 18 Aug 2021
Abstract
The paper considers the possibilities, prospects, and drawbacks of the mixed reality (MR) technology application using mixed reality smartglasses Microsoft HoloLens 2. The main challenge was to find and develop an approach that would allow surgeons to conduct operations using mixed reality on
[...] Read more.
The paper considers the possibilities, prospects, and drawbacks of the mixed reality (MR) technology application using mixed reality smartglasses Microsoft HoloLens 2. The main challenge was to find and develop an approach that would allow surgeons to conduct operations using mixed reality on a large scale, reducing the preparation time required for the procedure and without having to create custom solutions for each patient. Research was conducted in three clinical cases: two median neck and one branchial cyst excisions. In each case, we applied a unique approach of hologram positioning in space based on mixed reality markers. As a result, we listed a series of positive and negative aspects related to MR surgery, along with proposed solutions for using MR in surgery on a daily basis.
Full article
(This article belongs to the Special Issue VR, AR, and 3-D User Interfaces for Measurement and Control)
►▼
Show Figures

Figure 1
Open AccessArticle
Energy-Efficient Joint Base Station Switching and Power Allocation for Smart Grid Based Hybrid-Powered CoMP-Enabled HetNet
Future Internet 2021, 13(8), 213; https://doi.org/10.3390/fi13080213 - 17 Aug 2021
Abstract
With the rapid proliferation of wireless traffic and the surge of various data-intensive applications, the energy consumption of wireless networks has tremendously increased in the last decade, which not only leads to more CO2 emission, but also results in higher operating expenditure.
[...] Read more.
With the rapid proliferation of wireless traffic and the surge of various data-intensive applications, the energy consumption of wireless networks has tremendously increased in the last decade, which not only leads to more CO2 emission, but also results in higher operating expenditure. Consequently, energy efficiency (EE) has been regarded as an essential design criterion for future wireless networks. This paper investigates the problem of EE maximisation for a cooperative heterogeneous network (HetNet) powered by hybrid energy sources via joint base station (BS) switching (BS-Sw) and power allocation using combinatorial optimisation. The cooperation among the BSs is achieved through a coordinated multi-point (CoMP) technique. Next, to overcome the complexity of combinatorial optimisation, Lagrange dual decomposition is applied to solve the power allocation problem and a sub-optimal distance-based BS-Sw scheme is proposed. The main advantage of the distance-based BS-Sw is that the algorithm is tuning-free as it exploits two dynamic thresholds, which can automatically adapt to various user distributions and network deployment scenarios. The optimal binomial and random BS-Sw schemes are also studied to serve as benchmarks. Further, to solve the non-fractional programming component of the EE maximisation problem, a low-complexity and fast converging Dinkelbach’s method is proposed. Extensive simulations under various scenarios reveal that in terms of EE, the proposed joint distance-based BS-Sw and power allocation technique applied to the cooperative and harvesting BSs performs around 15–20% better than the non-cooperative and non-harvesting BSs and can achieve near-optimal performance compared to the optimal binomial method.
Full article
(This article belongs to the Section Internet of Things)
►▼
Show Figures

Figure 1
Open AccessArticle
A Bayesian Analysis of the Inversion of the SARS-COV-2 Case Rate in the Countries of the 2020 European Football Championship
by
and
Future Internet 2021, 13(8), 212; https://doi.org/10.3390/fi13080212 - 17 Aug 2021
Abstract
While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place from 11 June to 11 July 2021. We studied the inversion in the decreased/increased rate of new SARS-COV-2 infections in the
[...] Read more.
While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place from 11 June to 11 July 2021. We studied the inversion in the decreased/increased rate of new SARS-COV-2 infections in the countries of the tournament, investigating the hypothesis of an association. Using a Bayesian piecewise regression with a Poisson generalized linear model, we looked for a changepoint in the timeseries of the new SARS-COV-2 cases of each country, expecting it to appear not later than two to three weeks after the date of their first match. The two slopes, before and after the changepoint, were used to discuss the reversal from a decreasing to an increasing rate of the infections. For 17 out of 22 countries (77%) the changepoint came on average 14.97 days after their first match (95% CI 12.29–17.47). For all those 17 countries, the changepoint coincides with an inversion from a decreasing to an increasing rate of the infections. Before the changepoint, the new cases were decreasing, halving on average every 18.07 days (95% CI 11.81–29.42). After the changepoint, the cases begin to increase, doubling every 29.10 days (95% CI 14.12–9.78). This inversion in the SARS-COV-2 case rate, which happened during the tournament, provides evidence in favor of a relationship.
Full article
(This article belongs to the Special Issue Software Engineering and Data Science)
►▼
Show Figures

Figure 1
Open AccessArticle
Resolving Persistent Packet Collisions through Broadcast Feedback in Cellular V2X Communication
by
and
Future Internet 2021, 13(8), 211; https://doi.org/10.3390/fi13080211 - 16 Aug 2021
Abstract
The Third Generation Partnership Project (3GPP) Release 16 defines the sensing-based semi-persistent scheduling (SPS) as the resource allocation scheme for Sidelink Mode 2 in New Radio (NR)-based vehicle-to-everything (V2X) communication. A well-known issue in Mode 2 is the persistent packet collision that results
[...] Read more.
The Third Generation Partnership Project (3GPP) Release 16 defines the sensing-based semi-persistent scheduling (SPS) as the resource allocation scheme for Sidelink Mode 2 in New Radio (NR)-based vehicle-to-everything (V2X) communication. A well-known issue in Mode 2 is the persistent packet collision that results from two or more vehicles repeatedly using the same resource for transmission. It may create serious safety problems when the vehicles are in a situation where only the broadcast safety beacons can assist in driving. To resolve this issue, a solution that relies on the feedback from neighboring vehicles is proposed, through which the vehicles suffering from persistent packet collisions can quickly part and select other resources. Extensive simulations show that the proposed broadcast feedback scheme reduces persistent packet collisions by an order of magnitude compared to SPS, and it is achieved without sacrificing the average packet reception ratio (PRR). Namely, it is the quality aspect (i.e., burstiness) of the packet collisions that the proposed scheme addresses rather than the quantity (i.e., total number of collision losses). By preventing extended packet loss events, the proposed scheme is expected to serve NR V2X better, which requires stringent QoS in terms of the information update delay thereby helping to reduce the chances of vehicle crashes.
Full article
(This article belongs to the Section Internet of Things)
►▼
Show Figures

Figure 1
Open AccessReview
Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues
Future Internet 2021, 13(8), 210; https://doi.org/10.3390/fi13080210 - 16 Aug 2021
Abstract
With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything
[...] Read more.
With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything from vehicles to the human body to smart homes to smart factories. Mobility of the nodes enhances the network coverage and connectivity. One of the crucial requirements in IoT systems is the accurate and fast localization of its nodes with high energy efficiency and low cost. The localization process has several challenges. These challenges keep changing depending on the location and movement of nodes such as outdoor, indoor, with or without obstacles and so on. The performance of localization techniques greatly depends on the scenarios and conditions from which the nodes are traversing. Precise localization of nodes is very much required in many unique applications. Although several localization techniques and algorithms are available, there are still many challenges for the precise and efficient localization of the nodes. This paper classifies and discusses various state-of-the-art techniques proposed for IoT node localization in detail. It includes the different approaches such as centralized, distributed, iterative, ranged based, range free, device-based, device-free and their subtypes. Furthermore, the different performance metrics that can be used for localization, comparison of the different techniques, some prominent applications in smart cities and future directions are also covered.
Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
►▼
Show Figures

Figure 1
Open AccessArticle
Crowdsourcing Framework for QoE-Aware SD-WAN
Future Internet 2021, 13(8), 209; https://doi.org/10.3390/fi13080209 - 15 Aug 2021
Abstract
Quality of experience (QoE) is an important measure of users’ satisfaction regarding their network-based services, and it is widely employed today to provide a real assessment of the service quality as perceived by the end users. QoE measures can be used to improve
[...] Read more.
Quality of experience (QoE) is an important measure of users’ satisfaction regarding their network-based services, and it is widely employed today to provide a real assessment of the service quality as perceived by the end users. QoE measures can be used to improve application performance, as well as to optimize network resources and reallocate them as needed when the service quality degrades. While quantitative QoE assessments based on network parameters may provide insights into users’ experience, subjective assessments through direct feedback from the users have also gathered interest recently due to their accuracy and interactive nature. In this paper, we propose a framework that can be used to collect real-time QoE feedback through crowdsourcing and forward it to network controllers to enhance streaming routes. We analyze how QoE can be affected by different network conditions, and how different streaming protocols compare against each other when the network parameters change dynamically. We also compare the real-time user feedback to predefined network changes to measure if participants will be able to identify all degradation events, as well as to examine which combination of degradation events are noticeable to the participants. Our aim is to demonstrate that real-time QoE feedback can enhance cloud-based services and can adjust service quality on the basis of real-time, active participants’ interactions.
Full article
(This article belongs to the Section Internet of Things)
►▼
Show Figures

Figure 1
Open AccessArticle
Secure Internal Data Markets
Future Internet 2021, 13(8), 208; https://doi.org/10.3390/fi13080208 - 12 Aug 2021
Abstract
The data market concept has gained a lot of momentum in recent years, fuelled by initiatives to set up such markets, e.g., on the European level. Still, the typical data market concept aims at providing a centralised platform with all of its positive
[...] Read more.
The data market concept has gained a lot of momentum in recent years, fuelled by initiatives to set up such markets, e.g., on the European level. Still, the typical data market concept aims at providing a centralised platform with all of its positive and negative side effects. Internal data markets, also called local or on-premise data markets, on the other hand, are set up to allow data trade inside an institution (e.g., between divisions of a large company) or between members of a small, well-defined consortium, thus allowing the remuneration of providing data inside these structures. Still, while research on securing global data markets has garnered some attention throughout recent years, the internal data markets have been treated as being more or less similar in this respect. In this paper, we outline the major differences between global and internal data markets with respect to security and why further research is required. Furthermore, we provide a fundamental model for a secure internal data market that can be used as a starting point for the generation of concrete internal data market models. Finally, we provide an overview on the research questions we deem most pressing in order to make the internal data market concept work securely, thus allowing for more widespread adoption.
Full article
(This article belongs to the Special Issue Big Data Security and Privacy: Opportunities, Challenges and Solutions)
►▼
Show Figures

Figure 1
Open AccessArticle
Securing SDN-Based IoT Group Communication
by
and
Future Internet 2021, 13(8), 207; https://doi.org/10.3390/fi13080207 - 09 Aug 2021
Abstract
IoT group communication allows users to control multiple IoT devices simultaneously. A convenient method for implementing this communication paradigm is by leveraging software-defined networking (SDN) and allowing IoT endpoints to “advertise” the resources that can be accessed through group communication. In this paper,
[...] Read more.
IoT group communication allows users to control multiple IoT devices simultaneously. A convenient method for implementing this communication paradigm is by leveraging software-defined networking (SDN) and allowing IoT endpoints to “advertise” the resources that can be accessed through group communication. In this paper, we propose a solution for securing this process by preventing IoT endpoints from advertising “fake” resources. We consider group communication using the constrained application protocol (CoAP), and we leverage Web of Things (WoT) Thing Description (TD) to enable resources’ advertisement. In order to achieve our goal, we are using linked-data proofs. Additionally, we evaluate the application of zero-knowledge proofs (ZKPs) for hiding certain properties of a WoT-TD file.
Full article
(This article belongs to the Special Issue Security and Privacy in Blockchains and the IoT)
►▼
Show Figures

Figure 1
Open AccessArticle
Factors Affecting e-Government Adoption by Dairy Farmers: A Case Study in the North-West of Spain
Future Internet 2021, 13(8), 206; https://doi.org/10.3390/fi13080206 - 05 Aug 2021
Abstract
With the objective of assessing the farmers’ situation regarding the use of the ICT and their relations with the electronic government, a case study consisting in the realization of 34 face-to-face surveys was conducted between February and March 2020 in dairy farms in
[...] Read more.
With the objective of assessing the farmers’ situation regarding the use of the ICT and their relations with the electronic government, a case study consisting in the realization of 34 face-to-face surveys was conducted between February and March 2020 in dairy farms in the region of Galicia (Spain). The sample was selected according to one of the most important online journals in the farming sector at a national level. From the census, we chose those farms considered most representative taking into account the main criteria: the level of PAC (Common Agrarian Politics) subsidies and milk production (litres/cow and year). The results show that the majority of the farmers used the internet, but on many an occasion, they were discontented in relation to the poor connection quality in their farms. In regard to the use of the electronic government for procedures related to their farms, many of them were able to perform them through the government website; however, there were procedures which the users defined as “complex” and which had to be outsourced to authorised entities. The results also show that the farmers do want to employ the e-government, mainly because of the time and cost saving; however, the current web pages do not meet the users’ expectations. Finally, this situation, applied to a region placed among the 10 most productive regions of milk, is comparable to what happens in other regions.
Full article
(This article belongs to the Topic Advances in Online and Distance Learning)
►▼
Show Figures

Figure 1
Open AccessArticle
Cascaded κ-μ Fading Channels with Colluding and Non-Colluding Eavesdroppers: Physical-Layer Security Analysis
by
and
Future Internet 2021, 13(8), 205; https://doi.org/10.3390/fi13080205 - 04 Aug 2021
Abstract
In this paper, the physical-layer security for a three-node wiretap system model is studied. Under the threat of multiple eavesdroppers, it is presumed that a transmitter is communicating with a legitimate receiver. The channels are assumed to be following cascaded -
[...] Read more.
In this paper, the physical-layer security for a three-node wiretap system model is studied. Under the threat of multiple eavesdroppers, it is presumed that a transmitter is communicating with a legitimate receiver. The channels are assumed to be following cascaded - fading distributions. In addition, two scenarios for eavesdroppers’ interception and information-processing capabilities are investigated: colluding and non-colluding eavesdroppers. The positions of these eavesdroppers are assumed to be random in the non-colluding eavesdropping scenario, based on a homogeneous Poisson point process (HPPP). The security is examined in terms of the secrecy outage probability, the probability of non-zero secrecy capacity, and the intercept probability. The exact and asymptotic expressions for the secrecy outage probability and the probability of non-zero secrecy capacity are derived. The results demonstrate the effect of the cascade level on security. Additionally, the results indicate that as the number of eavesdroppers rises, the privacy of signals exchanged between legitimate ends deteriorates. Furthermore, in this paper, regarding the capabilities of tapping and processing the information, we provide a comparison between colluding and non-colluding eavesdropping.
Full article
(This article belongs to the Special Issue Selected Papers from the International Conference on Communications, Signal Processing and Their Applications (ICCSPA ’20))
►▼
Show Figures

Figure 1
Open AccessArticle
A DFT-Based Running Time Prediction Algorithm for Web Queries
Future Internet 2021, 13(8), 204; https://doi.org/10.3390/fi13080204 - 04 Aug 2021
Abstract
Web search engines are built from components capable of processing large amounts of user queries per second in a distributed way. Among them, the index service computes the top-k documents that best match each incoming query by means of a document ranking
[...] Read more.
Web search engines are built from components capable of processing large amounts of user queries per second in a distributed way. Among them, the index service computes the top-k documents that best match each incoming query by means of a document ranking operation. To achieve high performance, dynamic pruning techniques such as the WAND and BM-WAND algorithms are used to avoid fully processing all of the documents related to a query during the ranking operation. Additionally, the index service distributes the ranking operations among clusters of processors wherein in each processor multi-threading is applied to speed up query solution. In this scenario, a query running time prediction algorithm has practical applications in the efficient assignment of processors and threads to incoming queries. We propose a prediction algorithm for the WAND and BM-WAND algorithms. We experimentally show that our proposal is able to achieve accurate prediction results while significantly reducing execution time and memory consumption as compared against an alternative prediction algorithm. Our proposal applies the discrete Fourier transform (DFT) to represent key features affecting query running time whereas the resulting vectors are used to train a feed-forward neural network with back-propagation.
Full article
(This article belongs to the Special Issue Parallel, Distributed and Grid/Cloud/P2P Computing)
►▼
Show Figures

Figure 1
Open AccessArticle
Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses
Future Internet 2021, 13(8), 203; https://doi.org/10.3390/fi13080203 - 04 Aug 2021
Abstract
A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can
[...] Read more.
A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can acquire quantitatively valuable knowledge about a research area by using bibliographic information on academic publications provided by bibliographic data providers. Bibliometric analyses include the calculation of bibliometric networks to describe affiliations or similarities of bibliometric entities (e.g., authors) and group them into clusters representing subareas or communities. Calculating and visualizing bibliometric networks is a nontrivial and time-consuming data science task that requires highly skilled individuals. In addition to domain knowledge, researchers must often provide statistical knowledge and programming skills or use software tools having limited functionality and usability. In this paper, we present the ambalytics bibliometric platform, which reduces the complexity of bibliometric network analysis and the visualization of results. It accompanies users through the process of bibliometric analysis and eliminates the need for individuals to have programming skills and statistical knowledge, while preserving advanced functionality, such as algorithm parameterization, for experts. As a proof-of-concept, and as an example of bibliometric analyses outcomes, the calculation of research fronts networks based on a hybrid similarity approach is shown. Being designed to scale, ambalytics makes use of distributed systems concepts and technologies. It is based on the microservice architecture concept and uses the Kubernetes framework for orchestration. This paper presents the initial building block of a comprehensive bibliometric analysis platform called ambalytics, which aims at a high usability for users as well as scalability.
Full article
(This article belongs to the Special Issue Towards Convergence of Internet of Things and Cyber-Physical Systems)
►▼
Show Figures

Figure 1
Highly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Sensors, Future Internet, Information, J. Imaging, MTI
Augmented and Mixed Reality
Editors-in-Chief: Andrea Sanna, Federico Manuri, Francesco De PaceDeadline: 31 May 2022
Topic in
Education Sciences, Future Internet, Information, J. Intell., Sustainability
Advances in Online and Distance Learning
Editors-in-Chief: Neil Gordon, Han ReichgeltDeadline: 31 July 2022
Conferences
Special Issues
Special Issue in
Future Internet
Global Trends and Advances Towards a Smarter Grid and Smart Cities-II
Guest Editor: Om P. MalikDeadline: 31 August 2021
Special Issue in
Future Internet
Recent Advances of Machine Learning Techniques on Smartphones
Guest Editors: Mehdi Sookhak, Rishi Saripalle, Mahboobeh HaghparastDeadline: 20 September 2021
Special Issue in
Future Internet
Distributed Ledger Technologies for IoT and Softwarized Networks
Guest Editors: Kien Nguyen, Xiaoyan Wang, Xun ShaoDeadline: 30 September 2021
Special Issue in
Future Internet
Interface Design Challenges for Smart Control Rooms
Guest Editors: Genoveffa Tortora, Giuliana Vitiello, Marco WincklerDeadline: 15 October 2021
Topical Collections
Topical Collection in
Future Internet
Featured Reviews of Future Internet Research
Collection Editor: Dino Giuli
Topical Collection in
Future Internet
Innovative People-Centered Solutions Applied to Industries
Collection Editors: Dino Giuli, Carlos Filipe Da Silva Portela
Topical Collection in
Future Internet
Information Systems Security
Collection Editor: Luis Javier Garcia Villalba





