2021_3 - Infocommunications

2021. 3^rd Issue

Volume XIII, Number 3

MESSAGE FROM THE EDITOR-IN-CHIEF

Pal Varga
From traffic analysis to system security: broad interest within the Infocommunications domain
THE TERM ”traffic analysis” may be misleading in this issue of Infocommunications Journal. Civilians naturally think it is something about analyzing vehicular transport on the roads – although for ICT practitioners it always has been about telco- or computer network traffic. Surprisingly though, the first two articles in this issue are actually discussing road transport traffic analysis. The methods we use in the infocommunications domain is now applied to the transport domain by our very own experts in the communications society. The third article in this issue is indeed, on (cellular) mobile network traffic. Mobile network in the the sense that the user equipment can be mobile; yet another way to get confused with transportation systems. The current issue of the journal features eight papers and 92 pages if counting the front and back covers as well. This makes the current issue the thickest so far – but not only in volume. Let us have a brief overview of the papers in this issue.

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PAPERS FROM OPEN CALL

Attila M. Nagy, Bernát Wiandt and Vilmos Simon
Transient-based automatic incident detection method for intelligent transport systems
One of the major problems of traffic in big cities today is the occurrence of congestion phenomena on the road network, which has several serious effects not only on the lives of drivers, but also on city inhabitants. In order to deal with these phenomena, it is essential to have an in-depth understanding of the processes that lead to the occurrence of congestion and its spilling over into contiguous areas of the city.

Reference
DOI: 10.36244/ICJ.2021.3.1
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Mehran Amini, Miklos F. Hatwagner, Gergely Mikulai, and Laszlo T. Koczy
Developing a macroscopic model based on fuzzy cognitive map for road traffic flow simulation
Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow is also notoriously known as a highly uncertain nonlinear and complex system. Even though applications of FCM in risk analysis have been presented in various engineering fields, this research aims at modeling road traffic flow based on macroscopic characteristics through FCM. Therefore, a simulation of variables involved with road traffic flow carried out through FCM reasoning on historical data collected from the e-toll dataset of Hungarian networks of freeways. The proposed FCM model is developed based on 58 selected freeway segments as the “concepts” of the FCM; moreover, a new inference rule for employing in FCM reasoning process along with its algorithms have been presented. The results illustrate FCM representation and computation of the real segments with their main road traffic-related characteristics that have reached an equilibrium point. Furthermore, a simulation of the road traffic flow by performing the analysis of customized scenarios is presented, through which macroscopic modeling objectives such as predicting future road traffic flow state, route guidance in various scenarios, freeway geometric characteristics indication, and effectual mobility can be evaluated.

Reference
DOI: 10.36244/ICJ.2021.3.2
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Khalil Mebarkia, and Zoltán Zsóka
QoS Impacts of Slice Traffic Limitation
Slicing is an essential building block of 5G networks and beyond. Different slices mean sets of traffic demands with different requirements, which need to be served over separated or shared network resources. Various service chaining methods applied to support slicing lead to different network load patterns, impacting the QoS experienced by the traffic. In this paper, we analyze QoS properties applying a theoretical model. We also suggest appropriate parameter setting policies in slice-aware service function chaining (SFC) algorithms to increase QoS. We evaluate several metrics in different analysis scenarios to show the advantages of the slice-aware approach.

Reference
DOI: 10.36244/ICJ.2021.3.3
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Yahieal Alnaiemy, and Lajos Nagy
A Novel UWB Monopole Antenna with Reconfigurable Band Notch Characteristics Based on PIN Diodes
Our design for a novel UWB monopole antenna structure with reconfigurable band notch characteristics based on PIN diodes is presented in this paper. The proposed antenna is comprised of a modified circular patch and a partial ground plane. The band-notch characteristics are achieved by etching a slot on the partial ground plane and inserting three PIN diodes into the slots for adjusting the operating antenna bands. The reconfigurability is achieved by adding three PIN diodes to obtain eight states with UWB, dual and triple operating bands which can be obtained by changing the PIN state from ON to OFF, and vice versa. The proposed design shows a simple biasing process to switch the frequency bands with insignificant gain variation and low radiation efficiency reduction. The reconfigurability of the frequency is accomplished by adjusting the effective slot length through modifying the PIN diodes states at the desired operating bands. The desired operating frequency bands can be obtained by switching the diodes. A systematic parametric study based on a numerical analysis is invoked to verify and refine the proposed performance. The proposed antenna is fabricated on FR-4 substrate with dimensions of 50×60×1 mm3. The proposed antenna performance was tested experimentally and compared to the simulated results from CSTMW based on FIT. Experimental results were in concordance with simulated results. We found that the proposed antenna design had simple geometry and it was easy to control the frequency bands to suit the applications of WiMAX and WiFi systems.

Reference
DOI: 10.36244/ICJ.2021.3.4
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Márton Czermann, Péter Trócsányi, Zsolt Kis, Benedek Kovács and László Bacsárdi
Demonstrating BB84 Quantum Key Distribution in the Physical Layer of an Optical Fiber Based System
Nowadays, widely spread encryption methods (e.g., RSA) and protocols enabling digital signatures (e.g., DSA, ECDSA) are an integral part of our life. Although recently developed quantum computers have low processing capacity, huge dimensions and lack of interoperability, we must underline their practical significance – applying Peter Shor’s quantum algorithm (which makes it possible to factorize integers in polynomial time) public key cryptography is set to become breakable. As an answer, symmetric key cryptography proves to be secure against quantum based attacks and with it quantum key distribution (QKD) is going through vast development and growing to be a hot topic in data security. This is due to such methods securely generating symmetric keys by protocols relying on laws of quantum physics.

Reference
DOI: 10.36244/ICJ.2021.3.5
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Gábor Árpád Németh and Máté István Lugosi
Test generation algorithm for the All-Transition-State criteria of Finite State Machines
In the current article a novel test generation algorithm is presented for deterministic finite state machine specifications based on the recently introduced All-Transition-State criteria. The size of the resulting test suite and the time required for test suite generation are investigated through analytical and practical analyses and are also compared to the Transition Tour, Harmonized State Identifiers and random walk test generation methods. The fault detection capabilities of the different approaches are also investigated with simulations applying randomly injected transfer faults.

Reference
DOI: 10.36244/ICJ.2021.3.6
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Silia Maksuti, Mario Zsilak, Markus Tauber and Jerker Delsing
Security and Autonomic Management in System of Systems
A system of systems integrates systems that function independently but are networked together for a period of time to achieve a higher goal. These systems evolve over time and have emergent properties. Therefore, even with security controls in place, it is difficult to maintain a required level of security for the system of systems as a whole because uncertainties may arise at runtime. Uncertainties can occur from internal factors, such as malfunctions of a system, or from external factors, such as malicious attacks. Self-adaptation is an approach that allows a system to adapt in the face of such uncertainties without human intervention. This work outlines the progress made towards security mitigation in system of systems using a generic autonomic management system to assist engineers in developing self-adaptive systems. The manuscript describes the proposed system design, its implementation as part of the Eclipse Arrowhead framework, and its functionality in a smart agriculture use case. The system is designed and implemented in such a way that it can be reused and extended for a variety of use cases without requiring major changes.

Reference
DOI: 10.36244/ICJ.2021.3.7
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Matthias Maurer, Andreas Festl, Bor Bricelj, Germar Schneider, and Michael Schmeja
AutoML for Log File Analysis (ALFA) in a Production Line System of Systems pointed towards Predictive Maintenance
Automated machine learning and predictive maintenance have both become prominent terms in recent years. Combining these two fields of research by conducting log analysis using automated machine learning techniques to fuel predictive maintenance algorithms holds multiple advantages, especially when applied in a production line setting. This approach can be used for multiple applications in the industry, e.g., in semiconductor, automotive, metal, and many other industrial applications to improve the maintenance and production costs and quality. In this paper, we investigate the possibility to create a predictive maintenance framework using only easily available log data based on a neural network framework for predictive maintenance tasks. We outline the advantages of the ALFA (AutoML for Log File Analysis) approach, which are high efficiency in combination with a low entry border for novices, among others. In a production line setting, one would also be able to cope with concept drift and even with data of a new quality in a gradual manner. In the presented production line context, we also show the superior performance of multiple neural networks over a comprehensive neural network in practice. The proposed software architecture allows not only for the automated adaption to concept drift and even data of new quality but also gives access to the current performance of the used neural networks.

Reference
DOI: 10.36244/ICJ.2021.3.8
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