Special Issue "Statistical Approaches for Reliability of Future Communication Systems and Networks"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Mario Di Mauro
E-Mail Website
Guest Editor
Department of Information and Electrical Engineering and Applied Mathematics (DIEM), University of Salerno, 84084 Fisciano, Italy
Interests: network security; network reliability/availability; statistical/ML techniques for network/protocol characterization
Prof. Dr. Fabio Postiglione
E-Mail Website
Guest Editor
Department of Information and Electrical Engineering and Applied Mathematics (DIEM), University of Salerno, 84084 Fisciano, Italy
Interests: applied statistics; Bayesian inference; degradation models; reliability; availability evaluation
Prof. Dr. Besmir Tola
E-Mail Website
Guest Editor
Department of Information Security and Communication Technology, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway
Interests: network dependability modeling and evaluation; network performance analysis; network resource orchestration; network security
Dr. Luigi De Simone
E-Mail Website
Guest Editor
Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80138 Napoli, Italy
Interests: dependability benchmarking; software fault injection testing; virtualization reliability; safety-critical systems
Prof. Dr. Roberto Natella
E-Mail Website
Guest Editor
Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80138 Napoli, Italy
Interests: software dependability; software fault injection; software aging and rejuvenation

Special Issue Information

Dear Colleagues,

Reliability aspects are of increasingly crucial importance across the hyperconnected technological world.

All modern paradigms and architectures, such as Cloud/Fog/Edge Computing, the Internet of Things, 5G/6G, Network Function Virtualization, and Network Slicing, must satisfy strict reliability and availability requirements to provide their services without interruption. Consequently, characterizing a technological system or a network architecture in terms of its ability to deal with anomalous events (e.g., faults, attacks, overload, and disaster) and recovering its functionalities is becoming a key issue. Different methodologies are useful to achieve this aim—from the classic statistical methods to the data-driven approaches—including modern deep learning techniques.

Due to the growing interest both of academia and industry in the broad field of Reliability Engineering, for this Special Issue, we encourage high-quality research contributions—both theoretical and experimental—and timely survey papers that pinpoint future research directions in this field.

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

  • Reliability, dependability, availability, performability, serviceability, maintainability, and resiliency for emerging network and system architectures;
  • Statistical methods for reliability and availability evaluation of emerging networks and systems;
  • Next-generation network survivability;
  • Reliability/availability aspects in the field of softwarized networks (NFV, SDN, and Network Slicing);
  • Maintainability for emerging networks and systems;
  • Data analysis for testbeds of emerging networks and systems;
  • Prognostics and health management techniques for future networks and systems;
  • Network and system resilience;
  • Fault detection and isolation in large-scale networks;
  • Anomaly detection techniques for networks and systems;
  • Reliability issues of communication protocols;
  • Fault tolerance techniques for emerging network architectures;
  • Design of dependable architectures;
  • Statistical learning for reliability assessment;
  • Machine learning and Artificial Intelligence techniques for reliability;
  • Fault diagnosis and prediction in future networks;
  • Algorithms for reliability of networks and systems;
  • High Availability issues in 5G/6G networks;
  • High Availability issues in Cloud/Fog/Edge Computing;
  • High Availability for IoT and sensors;
  • High Availability for vehicle-to-vehicle communication;
  • High availability/Costs/Energy consumption trade-off for emerging network and systems;
  • Reliability aspects for emerging paradigms (Industrial IoT, Smart and Green Environments, Industry 4.0);
  • Ultra-Reliable Services (6 nines and beyond);
  • Chaos Engineering for future network infrastructures;
  • Load, stress, and fault-injection testing for network services;
  • Fault localization and debugging in network services.

Dr. Mario Di Mauro
Prof. Dr. Fabio Postiglione
Prof. Dr. Besmir Tola
Dr. Luigi De Simone
Prof. Dr. Roberto Natella
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. Electronics is an international peer-reviewed open access semimonthly 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 1800 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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Research

Article
Cybersecurity in Automotive: An Intrusion Detection System in Connected Vehicles
Electronics 2021, 10(15), 1765; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10151765 - 23 Jul 2021
Viewed by 502
Abstract
Today’s modern vehicles are connected to a network and are considered smart objects of IoT, thanks to the capability to send and receive data from the network. One of the greatest challenges in the automotive sector is to make the vehicle secure and [...] Read more.
Today’s modern vehicles are connected to a network and are considered smart objects of IoT, thanks to the capability to send and receive data from the network. One of the greatest challenges in the automotive sector is to make the vehicle secure and reliable. In fact, there are more connected instruments on a vehicle, such as the infotainment system and/or data interchange systems. Indeed, with the advent of new paradigms, such as Smart City and Smart Road, the vision of Internet of Things has evolved substantially. Today, we talk about the V2X systems in which the vehicle is strongly connected with the rest of the world. In this scenario, the main aim of all connected vehicles vendors is to provide a secure system to guarantee the safety of the drive and persons against a possible cyber-attack. So, in this paper, an embedded Intrusion Detection System (IDS) for the automotive sector is introduced. It works by adopting a two-step algorithm that provides detection of a possible cyber-attack. In the first step, the methodology provides a filter of all the messages on the Controller Area Network (CAN-Bus) thanks to the use of a spatial and temporal analysis; if a set of messages are possibly malicious, these are analyzed by a Bayesian network, which gives the probability that a given event can be classified as an attack. To evaluate the efficiency and effectiveness of our method, an experimental campaign was conducted to evaluate them, according to the classic evaluation parameters for a test’s accuracy. These results were compared with a common data set on cyber-attacks present in the literature. The first experimental results, obtained in a test scenario, seem to be interesting. The results show that our method has good correspondence in the presence of the most common cyber-attacks (DDoS, Fuzzy, Impersonating), obtaining a good score relative to the classic evaluation parameters for a test’s accuracy. These results have decreased performance when we test the system on a Free State Attack. Full article
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Article
Reliable Multicast Based on Congestion-Aware Cache in ICN
Electronics 2021, 10(13), 1579; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10131579 - 30 Jun 2021
Viewed by 318
Abstract
Reliable multicast distribution is essential for some applications such as Internet of Things (IoT) alarm information and important file distribution. Traditional IP reliable multicast usually relies on multicast source retransmission for recovery losses, causing huge recovery delay and redundancy. Moreover, feedback implosion tends [...] Read more.
Reliable multicast distribution is essential for some applications such as Internet of Things (IoT) alarm information and important file distribution. Traditional IP reliable multicast usually relies on multicast source retransmission for recovery losses, causing huge recovery delay and redundancy. Moreover, feedback implosion tends to occur towards multicast source as the number of receivers grows. Information-Centric Networking (ICN) is an emerging network architecture that is efficient in content distribution by supporting multicast and in-network caching. Although ubiquitous in-network caching provides nearby retransmission, the design of cache strategy greatly affects the performance of loss recovery. Therefore, how to recover losses efficiently and quickly is an urgent problem to be solved in ICN reliable multicast. In this paper, we first propose an overview architecture of ICN-based reliable multicast and formulate a problem using recovery delay as the optimization target. Based on the architecture, we present a Congestion-Aware Probabilistic Cache (CAPC) strategy to reduce recovery delay by caching recently transmitted chunks during multicast transmission. Then, we propose NACK feedback aggregation and recovery isolation scheme to decrease recovery overhead. Finally, experimental results show that our proposal can achieve fully reliable multicast and outperforms other approaches in recovery delay, cache hit ratio, transmission completion time, and overhead. Full article
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