Special Issue "Networks, Communication, and Computing vol. 2"

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: 1 June 2020.

Special Issue Editor

Prof. Dr. Andras Farago
E-Mail Website
Guest Editor
Department of Computer Science, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, P.O. Box 830688, MS-EC31 Richardson, TX 75083-0688, USA
Interests: communication networks and their protocols; network design/analysis methods; algorithms; complexity
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Networks, communication, and computing have become ubiquitous and inseparable parts of everyday life. This Special Issue is devoted to the exploration of the many-faceted relationship of these areas. We will explore the current state-of-the-art of research in networks, communication, and computing, with a particular interest in the interactions among these fields.

Topics of interest for submission include, but are not limited to the following:

  • Coding techniques
  • Modeling and simulation of communication systems
  • Network architecture and protocols, optical fiber/microwave communication
  • Satellite communication
  • Wired and wireless communication
  • Wireless sensor networks and related topics
  • Artificial intelligence
  • Computer graphics and virtual reality
  • Speech/image processing
  • Data mining algorithms
  • Distributed computing
  • Grid and cloud computing
  • Software architecture
  • Bioinformatics
  • Evolutionary algorithms
  • Software engineering
  • Ubiquitous computing
  • Semantic web and related topics
  • Case studies about the interactions of networks, communication, and computing

Prof. Dr. Andras Farago
Guest Editor

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. Algorithms 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.

Keywords

  • Networks
  • Communication
  • Computing and algorithms
  • Computing applications
  • Modeling and simulation
  • Network architecture

Published Papers (1 paper)

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Research

Open AccessArticle
Citywide Cellular Traffic Prediction Based on a Hybrid Spatiotemporal Network
Algorithms 2020, 13(1), 20; https://doi.org/10.3390/a13010020 - 08 Jan 2020
Abstract
With the arrival of 5G networks, cellular networks are moving in the direction of diversified, broadband, integrated, and intelligent networks. At the same time, the popularity of various smart terminals has led to an explosive growth in cellular traffic. Accurate network traffic prediction [...] Read more.
With the arrival of 5G networks, cellular networks are moving in the direction of diversified, broadband, integrated, and intelligent networks. At the same time, the popularity of various smart terminals has led to an explosive growth in cellular traffic. Accurate network traffic prediction has become an important part of cellular network intelligence. In this context, this paper proposes a deep learning method for space-time modeling and prediction of cellular network communication traffic. First, we analyze the temporal and spatial characteristics of cellular network traffic from Telecom Italia. On this basis, we propose a hybrid spatiotemporal network (HSTNet), which is a deep learning method that uses convolutional neural networks to capture the spatiotemporal characteristics of communication traffic. This work adds deformable convolution to the convolution model to improve predictive performance. The time attribute is introduced as auxiliary information. An attention mechanism based on historical data for weight adjustment is proposed to improve the robustness of the module. We use the dataset of Telecom Italia to evaluate the performance of the proposed model. Experimental results show that compared with the existing statistics methods and machine learning algorithms, HSTNet significantly improved the prediction accuracy based on MAE and RMSE. Full article
(This article belongs to the Special Issue Networks, Communication, and Computing vol. 2)
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