2022_2 - Infocommunications

2022. 2^nd Issue

Volume XIV, Number 2

MESSAGE FROM THE EDITOR-IN-CHIEF

Pal Varga
The metrics of Infocommunications Journal keep improving
INFOCOMMUNICATIONS Journal has received its metrics for the last year, and we are happy to report that they all show an increasing trend. The citations have almost doubled, and the SCR index has improved 1.5 times compared to the previous period. The journal has kept its Q3 place that was gained last year. Although we have not received an official impact factor yet, the impact score is 1.16, which is a very good indicator – even makes us hopeful for the near future. We keep the scientific and publication standards of the Infocommunications Journal high and keep improving these metrics. The current issue is over 100 pages long, a record number for the journal.

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PAPERS FROM OPEN CALL

Ákos Leiter, Mohamad Saleh Salah, László Pap, and László Bokor
Survey on PMIPv6-based Mobility Management Architectures for Software-Defined Networking
Software-Defined Networking (SDN) has changed the network landscape. Meanwhile, IP-based mobility management still evolves, and SDN affects it dramatically. Integrating Proxy Mobile IPv6 (PMIPv6) – a network-based mobility management protocol – with the SDN paradigm has created several promising approaches. This paper will present an extensive survey on the joint research area of PMIPv6 and SDN mobility management by detailing the available SDN-integrated network-based techniques and architectures that intend to accelerate handover and mitigate service disruption of mobility events in softwareized telecommunication networks. The article also provides an overview of where PMIPv6 can be used and how SDN may help reach those ways.

Reference
DOI: 10.36244/ICJ.2022.2.1
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Abdulhalim Fayad and Tibor Cinkler
Cost-Effective Delay-Constrained Optical Fronthaul Design for 5G and Beyond
With the rapid growth of the telecom sector heading towards 5G and 6G and the emergence of high-bandwidth and time-sensitive applications, mobile network operators (MNOs) are driven to plan their networks to meet these new requirements in a cost-effective manner. The cloud radio access network (CRAN) has been presented as a promising architecture that can decrease capital expenditures (Capex) and operating expenditures (Opex) and improve network performance. The fronthaul (FH) is a part of the network that links the remote radio head (RRH) to the baseband unit (BBU); these links need high-capacity and low latency connections necessitating costeffective implementation. On the other hand, the transport delay and FH deployment costs increase if the BBU is not placed in an appropriate location. In this paper, we propose an integer linear program (ILP) that simultaneously optimizes BBU and FH deployment resulting in minimal capital expenditures (Capex). Simulations are run to compare the performance of star and tree topologies with the varying line of sight probabilities (LoS) and delay thresholds. We consider fiber-optic (FO) and free-space optics (FSO) technologies as FH for the CRAN. Finally, we provide an analysis of Opex and the total costs of ownership (TCO), i.e., a technoeconomic analysis.

Reference
DOI: 10.36244/ICJ.2022.2.2
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Kotaru Kiran and D. Rajeswara Rao
Analytical Review and Study on Various Vertical Handover Management Technologies in 5G Heterogeneous Network
In recent mobile networks, due to the huge number of subscribers, the traffic may occur rapidly; therefore, it is complex to guarantee the accurate operation of the network. On the other hand, the Fifth generation (5G) network plays a vital role in the handover mechanism. Handover management is a prominent issue in 5G heterogeneous networks. Therefore, the Handover approach relocates the connection between the user equipment and the consequent terminal from one network to another. Furthermore, the handover approaches manage each active connection for the user equipment. This survey offers an extensive analysis of 50 research papers based on existing handover approaches in the 5G heterogeneous network. Finally, existing methods considering conventional vertical handover management strategies are elaborated to improve devising effective vertical handover management strategies. Moreover, the possible future research directions in attaining efficient vertical handover management in a 5G heterogeneous network are elaborated.

Reference
DOI: 10.36244/ICJ.2022.2.3
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Tamás Kőnig and Lajos Nagy
Conducted emission simulation and measurement of interleaved DC-DC converters
Switching-Mode Power Supplies (SMPS) are often used to power on-board satellite payloads due to their good conversion efficiency. However, they emit radiated and conducted noise, which can disturb the operation of other payloads. The current ripple sum of the power supplies will appear on the power bus. There are many methods to reduce this summarized noise, one of them is to interleave the on-switching times of the converters. This ripple cancellation method can decrease the noise component on the switching frequency and on its upper harmonics. In this article we are going to demonstrate the effects of the distributed interleaving with a measurement platform consisting of two Pulse Width Modulation (PWM) controlled Buck controllers.

Reference
DOI: 10.36244/ICJ.2022.2.4
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Mohammad Bawaneh and Vilmos Simon
A Novel Time Series Representation Approach for Dimensionality Reduction
With the growth of streaming data from many domains such as transportation, finance, weather, etc, there has been a surge in interest in time series data mining. With this growth and massive amounts of time series data, time series representation has become essential for reducing dimensionality to overcome the available memory constraints. Moreover, time series data mining processes include similarity search and learning of historical data tasks. These tasks require high computation time, which can be reduced by reducing the data dimensionality. This paper proposes a novel time series representation called Adaptive Simulated Annealing Representation (ASAR). ASAR considers the time series representation as an optimization problem with the objective of preserving the time series shape and reducing the dimensionality. ASAR looks for the instances in the raw time series that can represent the local trends and neglect the rest. The Simulated Annealing optimization algorithm is adapted in this paper to fulfill the objective mentioned above. We compare ASAR to three well-known representation approaches from the literature. The experimental results have shown that ASAR achieved the highest reduction in the dimensions. Moreover, it has been shown that using the ASAR representation, the data mining process is accelerated the most. The ASAR has also been tested in terms of preserving the shape and the information of the time series by performing One Nearest Neighbor (1-NN) classification and K-means clustering, which assures its ability to preserve them by outperforming the competing approaches in the K-means task and achieving close accuracy in the 1-NN classification task.

Reference
DOI: 10.36244/ICJ.2022.2.5
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Yasir Ahmed Idris Humad, and Levente Dudás
Wide Band Spectrum Monitoring System from 30MHz to 1800MHz with limited Size, Weight and Power Consumption by MRC-100 Satellite
Today, the usage of radio frequencies is steadily increasing based on the continuous development of modern telecommunication technologies, and this, in turn, increases the electromagnetic pollution not only on Earth but also in space. In low Earth orbit, electromagnetic pollution creates some kind of difficulty in controlling nano-satellites. So it is necessary to measure the electromagnetic pollution in the Low Earth Orbit. The basic aim of this paper is to present the capability of designing and developing a PocketQube-class satellite 3-PQ 5 x 5 x 15 cm as a potential continuation of SMOG-1, the fourth satellite of Hungary. The planned scientific payload of MRC- 100 is a wideband spectrum monitoring system for radio frequency smog in the frequency range of 30-2600 MHz on Low Earth Orbit (600 Km). In this paper, we have executed qualifying measurements on the whole system in the frequency range of 30-1800 MHz (first phase), and we calibrated its broadband antenna with a measurement system. We present the capabilities of the wideband spectrum monitoring system to measure radio frequency signals, with the limited size, weight, and power consumption of the designed system. The working spectrum measurement system was tested on the top of the roof of building V1 at BME University and An-echoic chamber, we were able to show that there is significant radio frequency smog caused by the upper HF band, FM band, VHF band, UHF band, LTE band, GSM band, 4G band, and UMTS band. This is relevant to the main mission target of MRC-100.

Reference
DOI: 10.36244/ICJ.2022.2.6
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Zoltán Pödör and Anna Szabó
A practical framework to generate and manage synthetic sensor data
A huge number of sensors are around us and they generate different kinds of data. Data owners, e.g. the companies need IT environments and applications to handle these datasets. The collected data often contain sensitive information about the operation of the companies and the production processes. Therefore, artificial sensor data are strongly needed in the development and testing phase of these applications. In this paper, we introduce a complex application with three main modules to manage synthetic sensor data. The first component is the data generator module, which is capable of creating synthetic sensor data according to the user-defined distributions and parameters. The second module is in charge of storing the generated data in a flexible relational database, developed by us. The third component ensures the filtering and the visualization of the collected or generated data. A common interface was created to bring together the components and to provide a unified interface for the users. The adequate user management was an important aspect of our work. Accordingly, four different user types and authorities were defined.

Reference
DOI: 10.36244/ICJ.2022.2.7
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Tushig Bat-Erdene, Yazan N. H. Zayed, Xinyu Qiu, Ibrar Shakoor, Achref Mekni, Peter A. Kara, Maria G. Martini, Laszlo Bokor, and Aniko Simon
On the Quality of Experience of Content Sharing in Online Education and Online Meetings
The turn of the decade introduced a new era of global pandemics to the world through the appearance of COVID-19, which is still an active crisis at the time of this paper. As a countermeasure, the phenomena of home office and online education became not only widely available, but also mandatory in many countries. However, the performance, reliability and general usability of such real-time activities may be severely affected by unfavorable network conditions. In both contexts, content sharing is now a common practice, and the success of the related use cases may fundamentally depend on it. In this paper, we present our surveys and subjective studies on the Quality of Experience of content sharing in online education and online meetings. A total of 6 surveys and 5 experiments are detailed, addressing topics of student experience, user interface settings, sharing options of lecturers and employees of the private sector, the perceivable effects of network impairments and the related long-term adaptation, the rubber band effect of slide sharing, the overall perceived quality and the separate quality aspects of media loading times, and the preference between visual quality, average frame rate and frame rate uniformity. The findings of the subjective studies do not characterize the use cases of the investigated topics on a general, widely-applicable level, as only a single online platform is involved throughout the experiments. However, their experimental configurations are reinforced by comprehensive surveys and many results indicate statistically significant differences between the selected test conditions.

Reference
DOI: 10.36244/ICJ.2022.2.8
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Fatima Es-sabery, Khadija Es-sabery, Hamid Garmani, Junaid Qadir, and Abdellatif Hair
Evaluation of different extractors of features at the level of sentiment analysis
Sentiment analysis is the process of recognizing and categorizing the emotions being expressed in a textual source. Tweets are commonly used to generate a large amount of sentiment data after they are analyzed. These feelings data help to learn about people's thoughts on a various range of topics. People are typically attracted for researching positive and negative reviews, which contain dislikes and likes, shared by the consumers concerning the features of a certain service or product. Therefore, the aspects or features of the product/ service play an important role in opinion mining. Furthermore to enough work being carried out in text mining, feature extraction in opinion mining is presently becoming a hot research field. In this paper, we focus on the study of feature extractors because of their importance in classification performance. The feature extraction is the most critical aspect of opinion classification since classification efficiency can be degraded if features are not properly chosen. A few scientific researchers have addressed the issue of feature extraction. And we found in the literature that almost every article deals with one or two feature extractors. For that, we decided in this paper to cover all the most popular feature extractors which are BOW, N-grams, TF-IDF, Word2vec, GloVe and FastText. In general, this paper will discuss the existing feature extractors in the opinion mining domain. Also, it will present the advantages and the inconveniences of each extractor. Moreover, a comparative study is performed for determining the most efficient combination CNN/extractor in terms of accuracy, precision, recall, and F1 measure.

Reference
DOI: 10.36244/ICJ.2022.2.9
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