Vol 10, No 3 (2024)

The review sets the task of analyzing existing solutions for communication systems based on Vehicle-to-Everything (V2X) technology using clustering and edge computing mechanisms in order to determine the conceptual model of the V2X system and the most significant indicators of quality of service (QoS), taking into account the application of the specified complex of technological solutions. The novelty of the work lies in the fact that the research is aimed at identifying the possibilities of integrating clustering mechanisms, edge and fog computing to determine optimal solutions for the deployment of roadside network infrastructure objects while maintaining high QoS indicators for communication equipment of this type. The result is that a scientifically based technological approach to constructing a conceptual model of a V2X system with specified QoS indicators has been proposed. Practical and theoretical relevance. The results obtained can be used in the design and deployment of V2X systems.

Relevance: In the context of the growing fleet of data center equipment, the development of IMT-2020 networks and the imminent emergence of Telepresence services of IMT-2030 networks, a particularly relevant area of modern research is the search for non-trivial, non-standard approaches and solutions in the field of provision of computing and network resources. This article covers current issues in the infrastructure direction of IMT-2030 networks - dynamic fog computing. The contribution of this technology to improve the efficiency of used resources is considered, and current scenarios for IMT-2030 networks are presented. In particular, we study the problem of searching for a group of devices in the computing fog for subsequent migration of typical FaaS platform containers. Problem statement: Research on the joint use of serverless architecture and dynamic fog computing for efficient load distribution of telepresence services. Goal of the work: Research and development of an effective method for distributing a group of microservices in dynamic fog computing. Methods: the algorithms under study belong to the type of metaheuristic algorithms for solving multicriteria optimization problems. To test the method, a laboratory network segment was developed, which served as a generator of real data on the operation of the tested platforms under conditions of increasing load. Based on a series of experiments, data was collected that formed the basis for subsequent modeling of the proposed method, which in turn was implemented in the Python programming language. Result: Analysis of the results showed the effectiveness of the proposed method within the framework of the task, which ultimately makes it possible to make a decision on migration many times faster. Novelty: A model and method for serverless architecture have been developed for migrating groups of microservices to groups of fog computing devices, under conditions of their mobility, and a meta-heuristic algorithm of a pack of gray wolves has been used to determine a group of devices for subsequent migration of typical microservices. Practical significance: The developed model and method can be used in the implementation of fog Computing, in conditions of device mobility, including in order to achieve the requirements of promising Telepresence services.

Relevance: The work addresses the problems of broadband modulation in relation to multiple access problems. The advantages of code multiplexing in the process of expanding the signal spectrum are indicated, which, as shown in the work, is a promising method of parallel data transmission. Purpose: The purpose of this work is, firstly, to increase the efficiency of using address sequences to identify the sender and recipient of information; secondly, to organize a parallel data transmission process from one node to many, ensuring the anonymity of the recipient and, thirdly, maintaining a low peak signal factor. Statement of the problem: The objectives of the work include the selection of address code structures, which, at two stages of expanding the signal spectrum, should solve the issues of identifying senders and recipients of information in the network at the physical level. It is required to build a system model that will ensure parallel data transfer from one node to many. An important requirement in such a multiple access network should be the ability to use modulation with the lowest signal crest factor. Methods: This work proposes two-stage wideband modulation using the direct spread spectrum method, where each sending node first generates an equivalent Gold code as the sum of sequences of maximum length addressed to recipient nodes, and then uses an address sequence identifying itself from set of orthogonal signals. The paper proposes methods for processing spectrum-expanding sequences based on the dual basis of the Galois field, which make it possible to quite effectively isolate information intended for each recipient. Results: A model of a parallel data transmission system with multiple access based on two-stage spectrum expansion is proposed. Identification of senders and recipients of information is carried out by mechanisms for the formation of address signal-code structures at the physical level. It is possible to implement a model with anonymous recipients, when any of the recipient nodes does not have information about the data addressed to other nodes. Also, this model does not contradict the use of the most noise-resistant type of modulation BPSK (or QPSK in single-bit transmission mode), which is designed to provide an extremely low signal crest factor. Novelty: A fundamentally new method of addressing at the physical level for a network with parallel information transmission is proposed, which increases the efficiency of using the frequency range. Theoretical and practical significance: The results obtained in the work, in the future, can be used in the construction of various highly noise-resistant networks with multiple access, where an important requirement is, first of all, an extremely low crest factor of the data source signal. Such networks include, in particular, networks formed by swarms of UAVs.

Relevance. Information about the electrical characteristics of the underlying surface has a significant impact on the calculations results of the radio tracks energy parameters in the very low frequency band. Currently, various versions of developed digital maps can potentially improve the accuracy of calculations and simplify the operator's activities in the initial data input. However, the capabilities of digital cartography are not integrated into existing forecasting techniques. The purpose of the study is to reduce the number of manual operations during the forecasting of the radio tracks energy parameters in the very low frequency band by developing a technique that allows to automate the input of the underlying surface electrical parameters. Methods. In this study we used methods of mathematical statistics to choose the quantization levels of radio tracks electrical parameters rationally. We used an interpolation method with a given decimation coefficient to obtain an electrical characteristics profile that meets the requirements of the forecasting methodology. Result. We selected the levels and quantization intervals of the underlying surface electrical characteristics which are needed to obtain the horizontal profiles, using statistical estimates. Further, we performed interpolation with the «nearest neighbor» method with a given decimation coefficient to exclude areas with frequent changes in the profiling parameters values. The decimation coefficient relies on the condition that the smallest length of a homogeneous section should not be less than the wavelength. The developed technique is implemented in the Matlab modeling environment as a combination of scripts and auxiliary functions. We provided an example of the technique application as the forecasting the ground wave field strength on a heterogeneous track. The novelty lies in the development of an original technique that provides rational profiling of the underlying surface electrical conductivity and dielectric permittivity for the subsequent usage of the obtained data in the forecasting the radio tracks energy parameters in the very low frequency band. Practical significance. The developed technique makes it possible to reduce the operator load during the initial data input and increases the accuracy of presenting this data. The technique can be used in a wavehop method for the predicting the radio tracks energy parameters to determine the vector sum of spatial and ground waves at the receiver.

Problem statement: designing the defense mechanism against coordinated behavior strategy attacks for mobile multiagent robotic systems. Possible attacks of that kind may be carried out by use message interception, creating and transmitting disinformation, and other actions, that does not have identifiable characteristics of saboteur intrusion, and lead to making incorrect or non-optimal decision by group of robots. The purpose of the work: the increase of probability of detection coordinated behavior strategy attacks on mobile multiagent robotic systems. Methods used: proposed algorithm is further development of self organization mechanism, using trust and reputation metrics for detection and counteraction against malicious robots. Accuracy of proposed method is confirmed using imitation model of collective exploration task. The novelty: algorithm is based on quantification of consensus achievement process into consecutive time periods, which is followed by inter- and intraperiod processing of information, produces by robots of the swarm and by malicious robots during communication. The result: experiment shows that the swarm is capable to counteract against coordinated attack of malicious robots, when concentration of malicious units is more than 51 %. The probability of such counteraction is close to 1. Known detection and counteraction methods for destructive informational influence in homogeneous swarms of robots prove to be effective in cases, when concentration of malicious units is less than 45 %. Practical significance: developed algorithm may be used for multiagent robotic systems security system design to protect against attack, executed during interactions between agents of the swarm. Algorithm allows to successfully counteract coordinated attacks similar to «51 percent attack».

Relevance. Changes in the fractal dimension of network traffic can serve as an indicator of attacks or anomalous activity. Fractal analysis allows to identify changes in the temporal structure of traffic and signal possible threats. The self-similarity observed over wide time scales indicates the multifractal nature of the anomalies, which requires further study. Thus, the development of methods for detecting and classifying cyber attacks using multifractal analysis is an urgent task to improve information security.The aim of the article. Increasing the efficiency of detection and classification of computer attacks in IoT networks using machine learning methods by expanding the number of attributes characterizing the parameters of the multifractal spectrum of fractal dimension.Research methods: discrete wavelet analysis, multifractal analysis, machine learning, software implementation of a combined multiclass classification method in conjunction with fractal analysis methods.Results. A methodology has been developed for assessing the characteristics of the multifractal spectrum of the fractal dimension of traffic using a sequence of current estimates of the fractal dimension in an analysis window of a fixed length depending on the resolution interval (sampling time). The analytical results of experimental assessments of multifractal analysis of processed processes in IoT networks are presented. The informational significance of additional attributes of computer attacks and normal traffic is assessed for the case of binary and multi-class classification using the Gini index for two cases: without adding a multifractal spectrum of fractal dimension and with the addition of a multifractal spectrum of fractal dimension. It has been shown that the main concentration of the most significant attributes falls on the sampling interval of 500 ms...1.5 s.Novelty. The concept of a multifractal spectrum of fractal dimension is introduced in the form of a sequence of current estimates of the fractal dimension in an analysis window of a fixed length depending on the resolution interval.Practical significance. The presented method for estimating the parameters of a multifractal spectrum of fractal dimension is universal and can be applied in various information systems.