Special Issue "Smart Computing for Smart Cities (SC2)"

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: closed (22 October 2020).

Special Issue Editors

Dr. Anish Jindal
E-Mail Website
Guest Editor
School of Computer Science & Electronic Engineering, University of Essex, UK
Interests: Ad-hoc Networks; Cyber-physical Systems; Data Analytics; Smart Grid; Security
Dr. Angelos Marnerides
E-Mail Website
Guest Editor
University of Glasgow, Scotland, UK
Interests: traffic characterization; network resilience; network security; anomaly detection; traffic classification
Special Issues and Collections in MDPI journals
Dr. Petros Spachos
E-Mail Website
Guest Editor
School of Engineering, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
Interests: wireless networking; mobile systems; Internet of Things (IoT)
Dr. Amit Dvir
E-Mail Website
Guest Editor
Department of Computer Science, Ariel Cyber Innovation Center (ACIC), Ariel University
Interests: Network communication; Wireless communication; Network security

Special Issue Information

Dear Colleagues,

We are inviting papers from researchers working on the themes presented in the 1st International Workshop on Smart Computing for Smart Cities (SC2) to be held on 15–18 June 2020, Cork, Ireland. For more information about the workshop, please use this link:

https://sites.google.com/view/sc2-wowmom.

The authors of selected papers presented at the workshop are invited to submit their extended versions to this Special Issue of the journal Computers after the conference. All selected papers will be free of charge if they are accepted after peer review. Submitted papers should be extended to the size of regular research or review articles, with at least a 50% extension of new results. All submitted papers will undergo our standard peer-review procedure. Accepted papers will be published in open access format in Computers and collected together in this Special Issue website. There are no page limitations for this journal.

Moreover, the call is open for all researchers and not just limited to papers presented at the workshop.

We are inviting original research work covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in Smart Computing for Smart Cities. The main topics include but are not limited to:

  • Data analytics in smart cities;
  • Resource management using smart computing for smart cities;
  • Network management in smart cities;
  • Novel communication architectures for smart city applications;
  • Increasing resilience and scalability in smart-city-based computing paradigms;
  • Analytical applications for improving security in smart cities;
  • Improving quality of service in smart cities using smart computing;
  • Self-healing and optimization techniques for communication infrastructure for ensuring sustainability in smart cities;
  • Prototypes and testbeds implementing smart computing to test various solutions in smart cities;
  • Smart fog/edge/cloud-based service solutions for the Internet of Things in smart cities;
  • Network load management in smart cities;
  • Machine learning for smart computing;
  • Analysis of computation requirements for smart-city-based applications;
  • Trust management between various devices in smart computing;
  • Data processing in smart computing for automation of applications in smart cities.
Dr. Anish Jindal
Dr. Angelos Marnerides
Dr. Petros Spachos
Dr. Amit Dvir
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. Computers 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.

Published Papers (2 papers)

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Open AccessArticle
NADAL: A Neighbor-Aware Deep Learning Approach for Inferring Interpersonal Trust Using Smartphone Data
Computers 2021, 10(1), 3; https://0-doi-org.brum.beds.ac.uk/10.3390/computers10010003 - 24 Dec 2020
Viewed by 667
Abstract
Interpersonal trust mediates multiple socio-technical systems and has implications for personal and societal well-being. Consequently, it is crucial to devise novel machine learning methods to infer interpersonal trust automatically using mobile sensor-based behavioral data. Considering that social relationships are often affected by neighboring [...] Read more.
Interpersonal trust mediates multiple socio-technical systems and has implications for personal and societal well-being. Consequently, it is crucial to devise novel machine learning methods to infer interpersonal trust automatically using mobile sensor-based behavioral data. Considering that social relationships are often affected by neighboring relationships within the same network, this work proposes using a novel neighbor-aware deep learning architecture (NADAL) to enhance the inference of interpersonal trust scores. Based on analysis of call, SMS, and Bluetooth interaction data from a one-year field study involving 130 participants, we report that: (1) adding information about neighboring relationships improves trust score prediction in both shallow and deep learning approaches; and (2) a custom-designed neighbor-aware deep learning architecture outperforms a baseline feature concatenation based deep learning approach. The results obtained at interpersonal trust prediction are promising and have multiple implications for trust-aware applications in the emerging social internet of things. Full article
(This article belongs to the Special Issue Smart Computing for Smart Cities (SC2))
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Open AccessReview
Cybersecurity in Intelligent Transportation Systems
Computers 2020, 9(4), 83; https://0-doi-org.brum.beds.ac.uk/10.3390/computers9040083 - 13 Oct 2020
Viewed by 1200
Abstract
Intelligent Transportation Systems (ITS) are emerging field characterized by complex data model, dynamics and strict time requirements. Ensuring cybersecurity in ITS is a complex task on which the safety and efficiency of transportation depends. The imposition of standards for a comprehensive architecture, as [...] Read more.
Intelligent Transportation Systems (ITS) are emerging field characterized by complex data model, dynamics and strict time requirements. Ensuring cybersecurity in ITS is a complex task on which the safety and efficiency of transportation depends. The imposition of standards for a comprehensive architecture, as well as specific security standards, is one of the key steps in the evolution of ITS. The article examines the general outlines of the ITS architecture and security issues. The main focus of security approaches is: configuration and initialization of the devices during manufacturing at perception layer; anonymous authentication of nodes in VANET at network layer; defense of fog-based structures at support layer and description and standardization of the complex model of data and metadata and defense of systems, based on AI at application layer. The article oversees some conventional methods as network segmentation and cryptography that should be adapted in order to be applied in ITS cybersecurity. The focus is on innovative approaches that have recently been trying to find their place in ITS security strategies. These approaches includes blockchain, bloom filter, fog computing, artificial intelligence, game theory and ontologies. In conclusion, a correlation is made between the commented methods, the problems they solve and the architectural layers in which they are applied. Full article
(This article belongs to the Special Issue Smart Computing for Smart Cities (SC2))
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