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: 30 May 2019

Special Issue Editors

Guest Editor
Prof. Dr. Xu An Wang

Key Laboratory for Network and Information Security, Engineering University of Chinese Armed Police Force, Xi’an, China
Website | E-Mail
Interests: Cloud computation; information security; cryptography; social network and media; blockchain, Internet of Things
Guest Editor
Dr. Massimo Ficco

Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy
Website | E-Mail
Interests: Cloud security and mobile computing
Guest Editor
Dr. Juggapong Natwichai

Chiang Mai University, Thailand
Website | E-Mail
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 1000 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.


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

Published Papers (1 paper)

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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
Received: 28 December 2018 / Revised: 1 March 2019 / Accepted: 4 March 2019 / Published: 8 March 2019
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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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