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Future Internet, Volume 12, Issue 8 (August 2020) – 18 articles

Cover Story (view full-size image): Named data networking (NDN), where addressable content name is used, is considered a candidate of next-generation internet architectures. NDN routers use in-network cache to replicate and store passing packets to make a faster content delivery. Because NDN uses a human-readable name, it is easy for an adversary to guess what kind of content is requested. To solve this issue, we developed a PEKS-based strategy for forwarding packets, where PEKS stands for public key encryption with keyword search. We implemented the PEKS-based strategy based on the best route strategy and multicast strategy of NDN and showed the performance of the PEKS-based NDN strategy. Our proposed PEKS-based NDN strategy provides higher privacy preservation, there is no master secret key which can be used to derive private keys, and PEKS_based NDN still allows in-network caching. View this paper.
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Article
From Color-Avoiding to Color-Favored Percolation in Diluted Lattices
Future Internet 2020, 12(8), 139; https://doi.org/10.3390/fi12080139 - 18 Aug 2020
Viewed by 1000
Abstract
We study the problem of color-avoiding and color-favored percolation in a network, i.e., the problem of finding a path that avoids a certain number of colors, associated with vulnerabilities of nodes or links, or is attracted by them. We investigate here regular (mainly [...] Read more.
We study the problem of color-avoiding and color-favored percolation in a network, i.e., the problem of finding a path that avoids a certain number of colors, associated with vulnerabilities of nodes or links, or is attracted by them. We investigate here regular (mainly directed) lattices with a fractions of links removed (hence the term “diluted”). We show that this problem can be formulated as a self-organized critical problem, in which the asymptotic phase space can be obtained in one simulation. The method is particularly effective for certain “convex” formulations, but can be extended to arbitrary problems using multi-bit coding. We obtain the phase diagram for some problem related to color-avoiding percolation on directed models. We also show that the interference among colors induces a paradoxical effect in which color-favored percolation is permitted where standard percolation for a single color is impossible. Full article
(This article belongs to the Special Issue Selected Papers from the INSCI2019: Internet Science 2019)
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Article
Enabling the Secure Use of Dynamic Identity for the Internet of Things—Using the Secure Remote Update Protocol (SRUP)
Future Internet 2020, 12(8), 138; https://doi.org/10.3390/fi12080138 - 18 Aug 2020
Cited by 2 | Viewed by 1100
Abstract
This paper examines dynamic identity, as it pertains to the Internet of Things (IoT), and explores the practical implementation of a mitigation technique for some of the key weaknesses of a conventional dynamic identity model. This paper explores human-centric and machine-based observer approaches [...] Read more.
This paper examines dynamic identity, as it pertains to the Internet of Things (IoT), and explores the practical implementation of a mitigation technique for some of the key weaknesses of a conventional dynamic identity model. This paper explores human-centric and machine-based observer approaches for confirming device identity, permitting automated identity confirmation for deployed systems. It also assesses the advantages of dynamic identity in the context of identity revocation permitting secure change of ownership for IoT devices. The paper explores use-cases for human and machine-based observation for authentication of device identity when devices join a Command and Control(C2) network, and considers the relative merits for these two approaches for different types of system. Full article
(This article belongs to the Special Issue Feature Papers for Future Internet—Internet of Things Section)
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Article
Progressive Teaching Improvement For Small Scale Learning: A Case Study in China
Future Internet 2020, 12(8), 137; https://doi.org/10.3390/fi12080137 - 17 Aug 2020
Cited by 2 | Viewed by 1115
Abstract
Learning data feedback and analysis have been widely investigated in all aspects of education, especially for large scale remote learning scenario like Massive Open Online Courses (MOOCs) data analysis. On-site teaching and learning still remains the mainstream form for most teachers and students, [...] Read more.
Learning data feedback and analysis have been widely investigated in all aspects of education, especially for large scale remote learning scenario like Massive Open Online Courses (MOOCs) data analysis. On-site teaching and learning still remains the mainstream form for most teachers and students, and learning data analysis for such small scale scenario is rarely studied. In this work, we first develop a novel user interface to progressively collect students’ feedback after each class of a course with WeChat mini program inspired by the evaluation mechanism of most popular shopping website. Collected data are then visualized to teachers and pre-processed. We also propose a novel artificial neural network model to conduct a progressive study performance prediction. These prediction results are reported to teachers for next-class and further teaching improvement. Experimental results show that the proposed neural network model outperforms other state-of-the-art machine learning methods and reaches a precision value of 74.05% on a 3-class classifying task at the end of the term. Full article
(This article belongs to the Special Issue Computational Thinking)
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Article
Coping Strategies and Anxiety and Depressive Symptoms in Young Adult Victims of Cyberstalking: A Questionnaire Survey in an Italian Sample
Future Internet 2020, 12(8), 136; https://doi.org/10.3390/fi12080136 - 12 Aug 2020
Cited by 2 | Viewed by 1458
Abstract
Aims: In the last decade, the use of smartphones, computers and devices has progressively increased, and prolonged use of technology and the internet has generated new arenas (and tools) for victimization. The first aim of this study was to analyze the use of [...] Read more.
Aims: In the last decade, the use of smartphones, computers and devices has progressively increased, and prolonged use of technology and the internet has generated new arenas (and tools) for victimization. The first aim of this study was to analyze the use of coping strategies in young adult self-declared victims of cyberstalking. The coping strategies were categorized as proactive behavior, avoidance tactics and passivity. To better understand these strategies, they were analyzed in light of the experience of victimization in terms of incurred misconduct. The second aim was to analyze the coping strategies and the consequences (in terms of depression and anxiety) that occurred in victims; a comparison was made between males and females. Methods: A self-administered questionnaire was distributed to over 433 young adults living in Italy. The questionnaires were filled out by 398 (92%) subjects, 41% males and 59% females. Their ages ranged from 18 to 30 years (M = 23.5, SD = 2.76). Respondents took part on a voluntary basis and did not receive any compensation (or extra credit) for their participation. Results: Findings from this investigation confirmed that among victims, females were more prone than males to experience cyberstalking (respectively, 65% and 35%), with females experiencing a higher percentage of more than one form of cyberstalking behavior than males. Young adult male victims used the internet principally for online gaming, and for this activity, they experienced more cyberstalking behavior than females. In most cases, the perpetrator was a male, and the victim–cyberstalker relationship was a friendship or an acquaintance. For the coping strategies adopted, the findings indicated that the victims were more prone to use avoidance tactics than proactivity behavior and passivity strategies. Young adults involved in this investigation mainly used avoidance tactics to cope with the stressful situation, which implies that they preferred to decrease the use of the internet or stop online contact than collect evidence and try to contact and reason with the cyberstalker or increase the misuse of alcohol of psychotropic substances. Moreover, females were less prone to use proactive behavior than expected. Our findings suggested that males were more prone than females to adopt passivity strategies, while females were more prone to adopt avoidance tactics. Moreover, the data showed that proactivity behavior was adopted more in the case of online contacts and online identity fraud, while passivity strategies were adopted in the case of online threats. Conclusion: Findings from this investigation show the importance of improving the knowledge about the coping strategies that could be suggested to victims and the impact on their psychological health. Full article
(This article belongs to the Special Issue Artificial Intelligence and Machine Learning in Cybercrime Detection)
Article
Understanding the Determinants and Future Challenges of Cloud Computing Adoption for High Performance Computing
Future Internet 2020, 12(8), 135; https://doi.org/10.3390/fi12080135 - 11 Aug 2020
Cited by 1 | Viewed by 1839
Abstract
High performance computing (HPC) is widely recognized as a key enabling technology for advancing scientific progress, industrial competitiveness, national and regional security, and the quality of human life. Notwithstanding this contribution, the large upfront investment and technical expertise required has limited the adoption [...] Read more.
High performance computing (HPC) is widely recognized as a key enabling technology for advancing scientific progress, industrial competitiveness, national and regional security, and the quality of human life. Notwithstanding this contribution, the large upfront investment and technical expertise required has limited the adoption of HPC to large organizations, government bodies, and third level institutions. Recent advances in cloud computing and telecommunications have the potential to overcome the historical issues associated with HPC through increased flexibility and efficiency, and reduced capital and operational expenditure. This study seeks to advance the literature on technology adoption and assimilation in the under-examined HPC context through a mixed methods approach. Firstly, the determinants of cloud computing adoption for HPC are examined through a survey of 121 HPC decision makers worldwide. Secondly, a modified Delphi method was conducted with 13 experts to identify and prioritize critical issues in the adoption of cloud computing for HPC. Results from the quantitative phase suggest that only organizational and human factors significantly influence cloud computing adoption decisions for HPC. While security was not identified as a significant influencer in adoption decisions, qualitative research findings suggest that data privacy and security issues are an immediate and long-term concern. Full article
(This article belongs to the Special Issue Cloud-Native Applications and Services)
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Article
Consortium Blockchain Smart Contracts for Musical Rights Governance in a Collective Management Organizations (CMOs) Use Case
Future Internet 2020, 12(8), 134; https://doi.org/10.3390/fi12080134 - 11 Aug 2020
Cited by 2 | Viewed by 2736
Abstract
Private and permissioned blockchains are conceptualized and mostly assembled for fulfilling corporations’ demands and needs in the context of their own premises. This paper presents a complete and sophisticated end-to-end permissioned blockchain application for governance and management of musical rights endorsed by smart [...] Read more.
Private and permissioned blockchains are conceptualized and mostly assembled for fulfilling corporations’ demands and needs in the context of their own premises. This paper presents a complete and sophisticated end-to-end permissioned blockchain application for governance and management of musical rights endorsed by smart contract development. In a music industry use case, this disclosed solution monitors and regulates conflicting musical rights of diverse entities under a popular permissioned distributed ledger technology network. The proposed implementation couples various and distinct business domains across the music industry organizations and non-profit blockchain associations. Full article
(This article belongs to the Special Issue Intelligent Innovations in Multimedia Data)
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Article
Multimodal Deep Learning for Group Activity Recognition in Smart Office Environments
Future Internet 2020, 12(8), 133; https://doi.org/10.3390/fi12080133 - 09 Aug 2020
Cited by 3 | Viewed by 1569
Abstract
Deep learning (DL) models have emerged in recent years as the state-of-the-art technique across numerous machine learning application domains. In particular, image processing-related tasks have seen a significant improvement in terms of performance due to increased availability of large datasets and extensive growth [...] Read more.
Deep learning (DL) models have emerged in recent years as the state-of-the-art technique across numerous machine learning application domains. In particular, image processing-related tasks have seen a significant improvement in terms of performance due to increased availability of large datasets and extensive growth of computing power. In this paper we investigate the problem of group activity recognition in office environments using a multimodal deep learning approach, by fusing audio and visual data from video. Group activity recognition is a complex classification task, given that it extends beyond identifying the activities of individuals, by focusing on the combinations of activities and the interactions between them. The proposed fusion network was trained based on the audio–visual stream from the AMI Corpus dataset. The procedure consists of two steps. First, we extract a joint audio–visual feature representation for activity recognition, and second, we account for the temporal dependencies in the video in order to complete the classification task. We provide a comprehensive set of experimental results showing that our proposed multimodal deep network architecture outperforms previous approaches, which have been designed for unimodal analysis, on the aforementioned AMI dataset. Full article
(This article belongs to the Section Internet of Things)
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Article
How Reputation Systems Change the Psychological Antecedents of Fairness in Virtual Environments
Future Internet 2020, 12(8), 132; https://doi.org/10.3390/fi12080132 - 09 Aug 2020
Cited by 1 | Viewed by 1216
Abstract
Reputational systems promote pro-social behaviors, also in virtual environments, therefore their study contributes to the knowledge of social interactions. Literature findings emphasize the power of reputation in fostering fairness in many circumstances, even when its influence is not directly oriented towards specific individuals. [...] Read more.
Reputational systems promote pro-social behaviors, also in virtual environments, therefore their study contributes to the knowledge of social interactions. Literature findings emphasize the power of reputation in fostering fairness in many circumstances, even when its influence is not directly oriented towards specific individuals. The present study contributes to the investigation of the psychological antecedents of fairness, introducing (or not) reputation in the social dilemma framework. Although reputational systems usually influence fairness dynamics, there are also socio-psychological characteristics that can play a role, affecting the adhesion to the norm online. To investigate their effects, we employed a virtual bargaining game that could include a reputational system depending on the experimental condition. Results show that the participant’s fairness could be significantly influenced by socio-psychological and demographic characteristics, as well as personality traits. Reputation seems to decrease fairness in those individuals who report high levels of Neuroticism and Openness. At the same time, high values of Self-Efficacy appear to be more likely associated with unfair behaviors when reputation is off the bargaining. Finally, Age and Sense of Community emerge as fairness promoters regardless of the experimental condition. Full article
(This article belongs to the Special Issue Selected Papers from the INSCI2019: Internet Science 2019)
Article
The Impact of English Learning Motivation and Attitude on Well-Being: Cram School Students in Taiwan
Future Internet 2020, 12(8), 131; https://doi.org/10.3390/fi12080131 - 06 Aug 2020
Viewed by 1745
Abstract
As English is a global language, it is important for students to learn it effectively and efficiently. Learning English from English cram schools is very popular in Taiwan. Most students have studied in English cram schools for some period of time of their [...] Read more.
As English is a global language, it is important for students to learn it effectively and efficiently. Learning English from English cram schools is very popular in Taiwan. Most students have studied in English cram schools for some period of time of their English learning experience. The present study concerns about how English cram school learners’ English learning attitudes related to their learning motivation and learning well-being in Taiwan. By using the quantitative research methodology, an empirical research model has been proposed and 277 valid questionnaires were collected. The research results show that learning motivation has a significant impact on learning attitude and learning well-being. Then, the English learning attitude provides mediated effects between learning motivation and well-being. Learning attitude is the key to English learning well-being. Furthermore, a participant’s gender has a significant moderating effect between learning intrinsic motivation and attitude. According to research findings, some suggestions such as using e-learning tools were provided for teachers and educators of the cram schools in Taiwan. Full article
(This article belongs to the Section Network Virtualization and Edge/Fog Computing)
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Article
A PEKS-Based NDN Strategy for Name Privacy
Future Internet 2020, 12(8), 130; https://doi.org/10.3390/fi12080130 - 31 Jul 2020
Cited by 1 | Viewed by 1532
Abstract
Named Data Networking (NDN), where addressable content name is used, is considered as a candidate of next-generation Internet architectures. NDN routers use In-Network cache to replicate and store passing packets to make faster content delivery. Because NDN uses a human-readable name, it is [...] Read more.
Named Data Networking (NDN), where addressable content name is used, is considered as a candidate of next-generation Internet architectures. NDN routers use In-Network cache to replicate and store passing packets to make faster content delivery. Because NDN uses a human-readable name, it is easy for an adversary to guess what kind of content is requested. To solve this issue, we develop a PEKS-based strategy for forwarding packets, where PEKS stands for public key encryption with keyword search. We implement the PEKS-based strategy based on the best route strategy and multicast strategy of NDN and show the performance of the PEKS-based NDN strategy. We also discuss the issues of the PEKS-based NDN strategy. Full article
(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy)
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Article
Challenges of PBFT-Inspired Consensus for Blockchain and Enhancements over Neo dBFT
Future Internet 2020, 12(8), 129; https://doi.org/10.3390/fi12080129 - 30 Jul 2020
Cited by 5 | Viewed by 3320
Abstract
Consensus mechanisms are a core feature for handling negotiation and agreements. Blockchain technology has seen the introduction of different sorts of consensus mechanism, ranging from tasks of heavy computation to the subtle mathematical proofs of Byzantine agreements. This paper presents the pioneer Delegated [...] Read more.
Consensus mechanisms are a core feature for handling negotiation and agreements. Blockchain technology has seen the introduction of different sorts of consensus mechanism, ranging from tasks of heavy computation to the subtle mathematical proofs of Byzantine agreements. This paper presents the pioneer Delegated Byzantine Fault Tolerance (dBFT) protocol of Neo Blockchain, which was inspired by the Practical Byzantine Fault Tolerance (PBFT). Besides introducing its history, this study describes proofs and didactic examples, as well as novel design and extensions for Neo dBFT with multiple block proposals. Finally, we discuss challenges when dealing with strong Byzantine adversaries, and propose solutions inspired on PBFT for current weak-synchrony problems and increasing system robustness against attacks. Key Contribution: Presents an overview of the history of PBFT-inspired consensus for blockchain, highlighting its current importance on the literature, challenges and assumptions. Contributes to the field of Distributed Consensus, proposing novel extensions for the Neo dBFT (dBFT 2.0+, dBFT 3.0 and dBFT 3.0+), with new insights on innovative consensus mechanisms. Full article
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Article
The Role of the CFO of an Industrial Company: An Analysis of the Impact of Blockchain Technology
Future Internet 2020, 12(8), 128; https://doi.org/10.3390/fi12080128 - 30 Jul 2020
Cited by 5 | Viewed by 2210
Abstract
This qualitative multiple case study explores the influence of blockchain technology on the chief financial officer (CFO) of an industrial company. Due to the advancing digitalization of business sectors and increasing competitive pressures, industrial companies are forced to promote their own digital transformation [...] Read more.
This qualitative multiple case study explores the influence of blockchain technology on the chief financial officer (CFO) of an industrial company. Due to the advancing digitalization of business sectors and increasing competitive pressures, industrial companies are forced to promote their own digital transformation to sustain on the market. Here, the literature regards the CFO as a key corporate function to induce digitization initiatives within organizations. The blockchain technology, due to its features of transparency, immutability and cryptography combined with its ability to coordinate data flows of e.g., the Internet of Things (IoT) or Artificial Intelligence (AI), constitutes a suitable instrument for the CFO to meet the requirements of Industry 4.0. This paper provides a contribution to address existing research gaps regarding the application side of blockchain technology. Thus, the objective of this work is to provide corporate financial functions, such as the CFO of an industrial company, with an understanding of the extent to which blockchain technology can be used for the role-specific responsibilities. Therefore, the underlying qualitative study explores the influence of blockchain technology on the CFO-function of an industrial company. Thus, intending to address a research gap on the application side, it asks (1) What is the impact of blockchain technology on the financial as well strategic role of the CFO? (2) What is the impact of blockchain technology in convergence with the Machine Economy on the key performance indicators (KPIs) of the CFO? (3) What is the impact of blockchain-enabled integrated business ecosystems on the role of the CFO? Based on a review of literature, semi-structured expert interviews were conducted with 23 participants. Analysis of the responses demonstrated a considerable impact of blockchain technology on the CFO-function. The results indicate improvements of business processes in regard to efficiency and automation, a relocation of the CFO’s strategic role, improvements of CFO-relevant KPIs through integrating machines into payment networks as well as the emergence of integrated business ecosystems facilitating new forms of inter-organizational collaboration. Necessary prerequisites for adoption include digital competences of the CFO, appropriate organizational structures, digital currencies and identities on the blockchain, a change of the competitive mindset as well as standardized platforms with a neutral governance. Full article
Article
Adaptive Allocation Algorithm for Multi-Radio Multi-Channel Wireless Mesh Networks
Future Internet 2020, 12(8), 127; https://doi.org/10.3390/fi12080127 - 29 Jul 2020
Cited by 1 | Viewed by 1179
Abstract
The wireless mesh network (WMN) has proven to be a great choice for network communication technology. WMNs are composed of access points (APs) that are installed and communicate with each other through multi-hop wireless networks. One or more of these APs acts as [...] Read more.
The wireless mesh network (WMN) has proven to be a great choice for network communication technology. WMNs are composed of access points (APs) that are installed and communicate with each other through multi-hop wireless networks. One or more of these APs acts as a gateway (GW) to the internet. Hosts of WMNs are stationary or mobile. According to the structure of WMNs, some network features may be affected, such as the overall performance, channel interference, and AP connectivity. In this paper, we propose a new adaptive channel allocation algorithm for a multi-radio multi-channel wireless mesh network. The algorithm is aimed to minimize the number of channel reassignments while maximizing the performance under practical constraints. The algorithm defines a decision function for the channel reassignments. The decision function aims to minimize the traffic around the GW. Whenever the traffic changes in the wireless mesh network, the decision function decides which channel radio reassignment should be done. We demonstrated the effectiveness of our algorithm through extensive simulations using Network Simulator 2 (NS-2). Full article
(This article belongs to the Section Smart System Infrastructure and Applications)
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Article
Data Lake Governance: Towards a Systemic and Natural Ecosystem Analogy
Future Internet 2020, 12(8), 126; https://doi.org/10.3390/fi12080126 - 27 Jul 2020
Cited by 1 | Viewed by 1566
Abstract
The realm of big data has brought new venues for knowledge acquisition, but also major challenges including data interoperability and effective management. The great volume of miscellaneous data renders the generation of new knowledge a complex data analysis process. Presently, big data technologies [...] Read more.
The realm of big data has brought new venues for knowledge acquisition, but also major challenges including data interoperability and effective management. The great volume of miscellaneous data renders the generation of new knowledge a complex data analysis process. Presently, big data technologies provide multiple solutions and tools towards the semantic analysis of heterogeneous data, including their accessibility and reusability. However, in addition to learning from data, we are faced with the issue of data storage and management in a cost-effective and reliable manner. This is the core topic of this paper. A data lake, inspired by the natural lake, is a centralized data repository that stores all kinds of data in any format and structure. This allows any type of data to be ingested into the data lake without any restriction or normalization. This could lead to a critical problem known as data swamp, which can contain invalid or incoherent data that adds no values for further knowledge acquisition. To deal with the potential avalanche of data, some legislation is required to turn such heterogeneous datasets into manageable data. In this article, we address this problem and propose some solutions concerning innovative methods, derived from a multidisciplinary science perspective to manage data lake. The proposed methods imitate the supply chain management and natural lake principles with an emphasis on the importance of the data life cycle, to implement responsible data governance for the data lake. Full article
(This article belongs to the Special Issue Selected Papers from the INSCI2019: Internet Science 2019)
Article
Improving Transaction Speed and Scalability of Blockchain Systems via Parallel Proof of Work
Future Internet 2020, 12(8), 125; https://doi.org/10.3390/fi12080125 - 27 Jul 2020
Cited by 6 | Viewed by 1988
Abstract
A blockchain is a distributed ledger forming a distributed consensus on a history of transactions, and is the underlying technology for the Bitcoin cryptocurrency. Its applications are far beyond the financial sector. The transaction verification process for cryptocurrencies is much slower than traditional [...] Read more.
A blockchain is a distributed ledger forming a distributed consensus on a history of transactions, and is the underlying technology for the Bitcoin cryptocurrency. Its applications are far beyond the financial sector. The transaction verification process for cryptocurrencies is much slower than traditional digital transaction systems. One approach to scalability or the speed at which transactions are processed is to design a solution that offers faster Proof of Work. In this paper, we propose a method for accelerating the process of Proof of Work based on parallel mining rather than solo mining. The goal is to ensure that no more than two or more miners put the same effort into solving a specific block. The proposed method includes a process for selection of a manager, distribution of work and a reward system. This method has been implemented in a test environment that contains all the characteristics needed to perform Proof of Work for Bitcoin and has been tested, using a variety of case scenarios, by varying the difficulty level and number of validators. Experimental evaluations were performed locally and in a cloud environment, and experimental results demonstrate the feasibility the proposed method. Full article
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Review
Scientific Development of Educational Artificial Intelligence in Web of Science
Future Internet 2020, 12(8), 124; https://doi.org/10.3390/fi12080124 - 24 Jul 2020
Cited by 16 | Viewed by 2045
Abstract
The social and technological changes that society is undergoing in this century are having a global influence on important aspects such as the economy, health and education. An example of this is the inclusion of artificial intelligence in the teaching–learning processes. The objective [...] Read more.
The social and technological changes that society is undergoing in this century are having a global influence on important aspects such as the economy, health and education. An example of this is the inclusion of artificial intelligence in the teaching–learning processes. The objective of this study was to analyze the importance and the projection that artificial intelligence has acquired in the scientific literature in the Web of Science categories related to the field of education. For this, scientific mapping of the reported documents was carried out. Different bibliometric indicators were analyzed and a word analysis was carried out. We worked with an analysis unit of 379 publications. The results show that scientific production is irregular from its beginnings in 1956 to the present. The language of greatest development is English. The most significant publication area is Education Educational Research, with conference papers as document types. The underlying organization is the Open University UK. It can be concluded that there is an evolution in artificial intelligence (AI) research in the educational field, focusing in the last years on the performance and influence of AI in the educational processes. Full article
(This article belongs to the Special Issue Distributed Systems and Artificial Intelligence)
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Article
Considerations on the Implications of the Internet of Things in Spanish Universities: The Usefulness Perceived by Professors
Future Internet 2020, 12(8), 123; https://doi.org/10.3390/fi12080123 - 24 Jul 2020
Cited by 3 | Viewed by 1521
Abstract
Internet of Things (IoT) is an emerging technology in the field of education, which has not yet been consolidated. Acceptance and adoption studies of IoT in higher education are scarce. Accordingly, the purpose of this study was to explore the acceptance of the [...] Read more.
Internet of Things (IoT) is an emerging technology in the field of education, which has not yet been consolidated. Acceptance and adoption studies of IoT in higher education are scarce. Accordingly, the purpose of this study was to explore the acceptance of the IoT by university professors for future adoption in higher education. An online survey was implemented based on the unified theory of acceptance and use of technology (UTAUT), in a sample of 587 Spanish university teachers, aged between 21 and 58. The results showed that performance expectancy, facilitating conditions, and attitude toward using technology were influential in behavioral intention to use IoT. While the intention for use was similar between men and women and with respect to age. However, in the different constructs of the UTAUT model, the highest average scores were obtained in men and in teachers over 36 years of age. Finally, the findings and implications of the paper are discussed, showing empirical evidence on the adoption and acceptance of IoT in higher education in the context of Spain, highlighting the need for further research on emerging technologies in a context that is marked by COVID-19. Full article
(This article belongs to the Section Internet of Things)
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Article
Hybrid Consensus Algorithm Based on Modified Proof-of-Probability and DPoS
Future Internet 2020, 12(8), 122; https://doi.org/10.3390/fi12080122 - 24 Jul 2020
Cited by 4 | Viewed by 1595
Abstract
As the core of blockchain technology, the consensus algorithm plays an important role in determining the security, data consistency, and efficiency of blockchain systems. The existing mainstream consensus algorithm is experiencing difficulties satisfying the needs of efficiency, security, and decentralization in real-world scenarios. [...] Read more.
As the core of blockchain technology, the consensus algorithm plays an important role in determining the security, data consistency, and efficiency of blockchain systems. The existing mainstream consensus algorithm is experiencing difficulties satisfying the needs of efficiency, security, and decentralization in real-world scenarios. This paper proposes a hybrid consensus algorithm based on modified Proof-of-Probability and Delegated Proof-of-Stake. In this method, the work of block generation and validation is, respectively, completed by the nodes using the modified Proof-of-Probability consensus algorithm and Delegated Proof-of-Stake consensus algorithm. When a transaction occurs, the system sends several target hash values to the whole network. Each modified Proof-of-Probability node has a different sorting algorithm, so they have different mining priorities. Every time a hash is decrypted by a modified Proof-of-Probability node, the modulo operation is done to the value of nonce, which is then compared with the expected value given by the supernode selected by the Delegated Proof-of-Stake nodes. If they are not the same, the Proof-of-Probability node enters the waiting time and the other Proof-of-Probability nodes continue to mine. By adopting two consensus algorithms, the malicious nodes must control more than 51% of the nodes that adopt the two consensus algorithms, at the same time, to effectively attack the system, that is, they must have more than 51% of the computing power and more than 51% of the tokens. This not only increases the cost of malicious attacks, but also reduces waste of computing power. In addition, the efficiency of the DPoS algorithm makes up for the deficiency of the PoP algorithm in system efficiency, and the mining behavior based on probability in the PoP algorithm also significantly weakens the ability of supernodes in the DPoS algorithm to conduct monopoly behavior or other malicious behaviors. In a word, the combination of the two algorithms makes the system perform better in terms of security, system efficiency, and decentralization. Full article
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