Special Issue "Advanced Techniques for Internet, P2P and Cloud Computing—selected papers from 3PGCIC-2018"

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (30 November 2019).

Special Issue Editors

Dr. Xu An Wang
Website
Guest Editor
Key Laboratory for Network and Information Security, Engineering University of Chinese Armed Police Force, Xi’an, China
Interests: cloud computation; information security; cryptography; social network and media; blockchain; Internet of Things
Special Issues and Collections in MDPI journals
Prof. Dr. Massimo Ficco
Website
Guest Editor
Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy
Interests: cloud security and mobile computing; data mining; big data; cyber security; network security
Special Issues and Collections in MDPI journals
Dr. Juggapong Natwichai
Website
Guest Editor
Chiang Mai University, Thailand
Interests: Big data, Security and Privacy

Special Issue Information

Dear Colleagues,

Internet, P2P, Grid and Cloud computing technologies have emerged as new paradigms for solving complex problems by enabling large-scale aggregation and sharing of computational, data and other geographically distributed computational resources. Rapid advances are being reported by many researchers and forums as regards understanding numerous issues in such paradigms, from theoretic to application aspects. The continuous development of Internet and the construction of new P2P and Grid and Cloud computing infrastructures are making possible the development of large scale applications from many fields of science and engineering.

In this special issue, we concentrate on the new developments of advanced techniques for Internet, P2P and Cloud Computing, in particular papers related with the following list of topics are encouraged to be submitted:

  1. Cloud computing and Grid computing
  2. P2P computing
  3. Client-server and web-based computing
  4. Internet-based computing
  5. Techniques for wireless network and mobile computing
  6. Advanced computing techniques for big data
  7. Advanced blockchain techniques
  8. Security, privacy and cryptographic techniques for Internet, P2P and Cloud computing
  9. Other advanced techniques for Internet, P2P and Cloud computing
Prof. Dr. Xu An Wang
Dr. Massimo Ficco
Dr. Juggapong Natwichai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Cloud computing
  • P2P computing
  • Internet computing
  • Blockchain technique
  • Security and privacy

Published Papers (6 papers)

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Research

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Open AccessArticle
Vehicular Delay-Tolerant Networks with Image Recognition-Based Adaptive Array Antenna for Winter Road Surveillance in Local Areas
Future Internet 2019, 11(9), 203; https://doi.org/10.3390/fi11090203 - 19 Sep 2019
Abstract
The rapid growth of the ITS (intelligent transport system) development requires us to realize new kinds of applications, such as the winter road surveillance system. However, it is still necessary to consider the network difficulty areas for LTE (long-term evolution) or 3G transmissions [...] Read more.
The rapid growth of the ITS (intelligent transport system) development requires us to realize new kinds of applications, such as the winter road surveillance system. However, it is still necessary to consider the network difficulty areas for LTE (long-term evolution) or 3G transmissions when one visits sightseeing spots such as ski resorts or spas in mountain areas. Therefore, this paper proposes a winter road surveillance system in the local area based on vehicular delay-tolerant networks. The adaptive array antenna controlled by image recognition with the Kalman filter algorithm is proposed as well to the system in order to realize higher delivery rates. The implementations of the prototype system are presented in this paper as well, and the effectivity of the radio transmission in the prototype system is realized by vehicular image recognition methods and the asynchronous voltage controls for antenna elements for the rapid directional controls of the radio transmission. The experimental results showed that the radio directional controls by the prototype system for the target vehicle can proceed within one second, and that the simulation with the GIS (geographic information system) map pointed out the delivery rates of the proposed method—which are better than those of the epidemic DTN (delay-tolerant networking) routing by the nondirectional antenna. The experiments of the proposed methods indicate a higher efficiency of the data transmissions—even in the mountain area. Furthermore, future research subjects are discussed in this paper. Full article
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Open AccessArticle
Distributed Uniform Streaming Framework: An Elastic Fog Computing Platform for Event Stream Processing and Platform Transparency
Future Internet 2019, 11(7), 158; https://doi.org/10.3390/fi11070158 - 19 Jul 2019
Cited by 7
Abstract
The increase of Internet of Things devices and the rise of more computationally intense applications presents challenges for future Internet of Things architectures. We envision a future in which edge, fog, and cloud devices work together to execute future applications. Because the entire [...] Read more.
The increase of Internet of Things devices and the rise of more computationally intense applications presents challenges for future Internet of Things architectures. We envision a future in which edge, fog, and cloud devices work together to execute future applications. Because the entire application cannot run on smaller edge or fog devices, we will need to split the application into smaller application components. These application components will send event messages to each other to create a single application from multiple application components. The execution location of the application components can be optimized to minimize the resource consumption. In this paper, we describe the Distributed Uniform Stream (DUST) framework that creates an abstraction between the application components and the middleware which is required to make the execution location transparent to the application component. We describe a real-world application that uses the DUST framework for platform transparency. Next to the DUST framework, we also describe the distributed DUST Coordinator, which will optimize the resource consumption by moving the application components to a different execution location. The coordinators will use an adapted version of the Contract Net Protocol to find local minima in resource consumption. Full article
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Open AccessArticle
Stacking-Based Ensemble Learning of Self-Media Data for Marketing Intention Detection
Future Internet 2019, 11(7), 155; https://doi.org/10.3390/fi11070155 - 10 Jul 2019
Cited by 6
Abstract
Social network services for self-media, such as Weibo, Blog, and WeChat Public, constitute a powerful medium that allows users to publish posts every day. Due to insufficient information transparency, malicious marketing of the Internet from self-media posts imposes potential harm on society. Therefore, [...] Read more.
Social network services for self-media, such as Weibo, Blog, and WeChat Public, constitute a powerful medium that allows users to publish posts every day. Due to insufficient information transparency, malicious marketing of the Internet from self-media posts imposes potential harm on society. Therefore, it is necessary to identify news with marketing intentions for life. We follow the idea of text classification to identify marketing intentions. Although there are some current methods to address intention detection, the challenge is how the feature extraction of text reflects semantic information and how to improve the time complexity and space complexity of the recognition model. To this end, this paper proposes a machine learning method to identify marketing intentions from large-scale We-Media data. First, the proposed Latent Semantic Analysis (LSI)-Word2vec model can reflect the semantic features. Second, the decision tree model is simplified by decision tree pruning to save computing resources and reduce the time complexity. Finally, this paper examines the effects of classifier associations and uses the optimal configuration to help people efficiently identify marketing intention. Finally, the detailed experimental evaluation on several metrics shows that our approaches are effective and efficient. The F1 value can be increased by about 5%, and the running time is increased by 20%, which prove that the newly-proposed method can effectively improve the accuracy of marketing news recognition. Full article
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Open AccessArticle
Web Browser Network Based on a BA Model for a Web-Based Virtual World
Future Internet 2019, 11(7), 147; https://doi.org/10.3390/fi11070147 - 05 Jul 2019
Cited by 2
Abstract
Real-time web applications such as a virtual world require considerable computing resources. However, as the number of servers increases, so does the maintenance and financial cost. To share tasks among web browsers, the browsers must share data. Therefore, a network must be constructed [...] Read more.
Real-time web applications such as a virtual world require considerable computing resources. However, as the number of servers increases, so does the maintenance and financial cost. To share tasks among web browsers, the browsers must share data. Therefore, a network must be constructed among the web browsers. In this paper, we propose the construction of a web browser network based on the Barabasi–Albert model (BA model). We focus on a web-based multiplayer online game that requires higher frequent communication and significant computing resources. We attempt to optimize computing resource utilization for web browsers. We improve upon the method in our previous study, which constructed a network for a web-based virtual world, using only location information. When a new user logged into a world, the web browser connected to two other browsers whose users had a location close to that of the user. The experimental results of that method showed 50% data coverage, which was insufficient to display the game screen because the web browser displays the characters on the virtual world. In this study, we attempt to use the BA model to construct more efficient networks than those in the previous study to increase data coverage. Our new method uses the number of connections of the web browser and location information to calculate the probability of web browser selection. The experimental results show that the data coverage exceeds 90%, indicating significant improvement over the previous method. Full article
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Open AccessArticle
Snack Texture Estimation System Using a Simple Equipment and Neural Network Model
Future Internet 2019, 11(3), 68; https://doi.org/10.3390/fi11030068 - 08 Mar 2019
Cited by 2
Abstract
Texture evaluation is manually performed in general, and such analytical tasks can get cumbersome. In this regard, a neural network model is employed in this study. This paper describes a system that can estimate the food texture of snacks. The system comprises a [...] Read more.
Texture evaluation is manually performed in general, and such analytical tasks can get cumbersome. In this regard, a neural network model is employed in this study. This paper describes a system that can estimate the food texture of snacks. The system comprises a simple equipment unit and an artificial neural network model. The equipment simultaneously examines the load and sound when a snack is pressed. The neural network model analyzes the load change and sound signals and then outputs a numerical value within the range (0,1) to express the level of textures such as “crunchiness” and “crispness”. Experimental results validate the model’s capacity to output moderate texture values of the snacks. In addition, we applied the convolutional neural network (CNN) model to classify snacks and the capability of the CNN model for texture estimation is discussed. Full article
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Review

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Open AccessReview
A Hybrid Adaptive Transaction Injection Protocol and Its Optimization for Verification-Based Decentralized System
Future Internet 2019, 11(8), 167; https://doi.org/10.3390/fi11080167 - 27 Jul 2019
Cited by 2
Abstract
Latency is a critical issue that impacts the performance of decentralized systems. Recently we designed various protocols to regulate the injection rate of unverified transactions into the system to improve system performance. Each of the protocols is designed to address issues related to [...] Read more.
Latency is a critical issue that impacts the performance of decentralized systems. Recently we designed various protocols to regulate the injection rate of unverified transactions into the system to improve system performance. Each of the protocols is designed to address issues related to some particular network traffic syndrome. In this work, we first provide the review of our prior protocols. We then provide a hybrid scheme that combines our transaction injection protocols and provides an optimal linear combination of the protocols based on the syndromes in the network. The goal is to speed up the verification process of systems that rely on only one single basic protocol. The underlying basic protocols are Periodic Injection of Transaction via Evaluation Corridor (PITEC), Probabilistic Injection of Transactions (PIT), and Adaptive Semi-synchronous Transaction Injection (ASTI). Full article
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