Problems of Informatization and Management

Analysis of load balancing algorithms in cloud computing

O.I. Shklyar — 2025-08-23

This article presents the results of a simulation-based study on the performance of various load balancing algorithms in a cloud service infrastructure using the CloudSim v7.0.0 platform. The simulated environment included one datacenter with 10 hosts, 50 virtual machines, and 200 cloudlet tasks. Seven load balancing algorithms were compared: Round Robin, Throttled Load Balancing, Active Monitoring, Weighted Least Connection, Biased Random Sampling, Min-Min, and Honeybee Foraging. Simulation outcomes were evaluated based on average task completion time, CPU utilization, load variance, and task migration count. Statistical analysis, including ANOVA and pairwise t-tests, revealed significant differences in algorithm efficiency. Based on the findings, further improvement directions for load balancing strategies are proposed, with a focus on adaptive and hybrid approaches.

Alternative approaches for smart contract upgradeability

R.O. Serebriakov — 2025-08-23

Smart contracts upgradeability is a critical requirement for modern decentralized applications based on blockchain technology, but its implementation remains a technical challenge due to the immutable nature of smart contracts. The Proxy Pattern has become the most widely used solution for implementing upgradability into smart contracts, but it comes with some limitations such as implementation complexity and strict memory layout inheritance. This paper introduces an alternative approach based on dynamic routing with Router Contract, which enables modular upgradeability through centralized address management, offering greater flexibility at the cost of requiring external state persistence. Furthermore, a hybrid architecture is proposed, combining both Proxy Pattern and Router Contract approaches to achieve dual-layer upgradeability – supporting both state-preserving updates and full module replacements. The paper offers a comprehensive evaluation of upgradeability strategies and proposes a versatile solution for evolving smart contract systems.

Technology of quality assessment of critical software systems based on ontological modeling

I.E. Raichev — 2025-08-23

The article investigates the problem of identifying and analyzing the requirements for program systems of critical purpose. For a variety of mission-critical system classes, the task of developing methods for verifying these systems for compliance with the specified requirements within the subject domain and analyzing risks and hazards throughout their life cycle is relevant. Compliance assessment is typically performed by evaluating the overall quality level of flight control software components during the testing phase. To comprehensively analyze the compliance of system attributes with the specified requirements, it is necessary to examine and structure a significant number of objects and functions. To address the problem of systematization within the subject domain, it is proposed to build a formal conceptual model of the system, based on which a set of objects, basic functions, and a quality model to assess the quality level of the system can be technologically formed.

The problem of improving the safety of the operation of objects controlled with automated flight control systems is still relevant. One way to achieve this goal is to ensure the quality and reliable functioning of the flight control systems, which is especially important during the operation of the tolerance control subsystem, which should ensure the complete implementation of control algorithms established for each type of aircraft. In the case of incorrect piloting and operation of units and equipment, there are risks to allow further flights to an unprepared crew or board of the aircraft, which has defects of equipment, which can cause an aviation incident that directly affects the safety of people's lives, as well as the integrity of the aircraft.

The way to solving the problem is the effective use of the ontological model of components of the flight control software systems to create a system of knowledge of the subject area of automated flight control systems. The article analyzes recent research and publications, which shows the effectiveness of using ontology to implement the decision-making process in the context of problematic ambiguity situations. For flight control systems, ontological research apparatus can be effectively used, as the main task of the software is to decide on the receipt of the control object during the flight in the state "within the admission" (regular regime) or "beyond tolerance".

The developed ontological model determines the composition, classification, structure and interconnection of requirements and risks and can forms a technological procedure for creating a quality model of critical PS and the concept of evaluating its characteristics and attributes. Ontological studies and created ontology directly indicate the quality properties that need to be included in the quality models and provide tools for constructing quality models: 1) Target quality model for the developer of the flight control system. 2) Quality in use model for the aircraft operator.

The conducted researches include: 1) Execution of ontological analysis of the subject area of application. 2) Creation of ontology of flight control software, which systematizes and structures knowledge of the concepts and objects of the subject area. 3) Formation of functions of interpretation of ontology, as well as specifications of criteria and restrictions for decision-making problems in critical systems. 4) Formation of specifications of requirements for reliability and safety of flight control systems based on the detection and generalization of components of risk analysis and dangers of functioning of critical software systems. 5)Construction of the target quality model and quality in use model for a given subject area and creation of methodology for evaluating the integral level of quality of flight control software.

The conclusions state that an ontological model and quality models can be used in the life cycle of different classes of control systems (including for certification), since any PS of control are characterized by the presence of a control object, which is controlled by a set of parameters measured by parametric information. The results, obtained in the article, can be apply by developers to create their own quality management system of any critical PS in different subject areas of application.

Further research is proposed to conduct a deeper analysis of the technology of integral assessment of the quality of the PS, especially in terms of normalization of metrics of quality attributes in order to unify them.

A method for expanding the reference model of open systems interaction

M.K. Pechurin — 2025-08-23

One type of aviation computer systems formed by a complex of interacting components placed on unmanned aircraft of light and ultralight classes is considered. A method is proposed to reduce the probability of loss of effective, in terms of the cost of production and operation, software and hardware support of the entire system, which can occur with the conscientious use of a multi-level reference model of open systems interaction . The method is based on the use of the morphological analysis method, for which the number of local components is proposed to be equal to the number of levels and sublevels, the search field is expanded for each level autonomously, without taking into account the relationships between levels, and the set of complete solutions of morphological analysis is formed by the classical operation of direct product. The resulting design allows you to determine, for example, by direct search using artificial intelligence tools, those elements (chains) of the display in which each variant of the implementation of the function for the higher levels corresponds to the variants of the implementation of functions and services for the lower levels, which determines the efficiency of the entire system.

Development of a model for forecasting web application vulnerabilities using machine learning methods

P.I. Melnychenko — 2025-08-23

With the increasing number of cyber threats, risk assessment based on vulnerability data has become a critical task. One of the main approaches involves the use of entropy methods and decision trees, which are applied to evaluate the degree of uncertainty and classify information. This study explores Shannon entropy and the decision tree construction algorithm for analyzing and predicting vulnerabilities. A decision tree model was developed to forecast future vulnerabilities based on a vulnerability dataset. Entropy was also calculated based on threat levels to quantitatively assess the uncertainty in the data.

Weighted checksum based method for fast burst error correction in wireless channels

O.P. Markovskyi — 2025-08-23

The method for fast correction of burst of errors in wireless data transmission channel for remote control computer systems has been proposed. Method is based on weighted checksums that low computational complexity provided.

The procedures of coding and burst error correction are developed and described in detail and illustrated by numerical example. The comparison analysis of the performance indicators of the proposed method with Reed-Solomon codes has been performed. It has been proved that the developed method provides reducing time of burst errors detection by two orders and time correction reducing by three orders ib comparing to Reed-Solomon codes.

This is of great practical importance in the implementation of control and correcting errors on the terminal microcontrollers of computed remote control systems equipped with single-chip radio modems.

N-phoneme model of speech signal recognition based on hidden Markov processes

O.Yu. Lavrynenko — 2025-08-23

This paper solves the urgent scientific problem of increasing the probability of recognizing commands and fused speech in radio engineering devices and telecommunications under the influence of distorting factors by developing new recognition models. It is proposed to use hidden Markov processes to conduct a probabilistic description of the one-, three-, and four-phoneme model of speech signal recognition, which makes it possible to theoretically estimate the probability of recognition using each of the models. On the basis of a comparative analysis, the four-phoneme model of speech signal recognition was investigated, which, by improving the three-phoneme model by adding one more state to the model, allows, unlike other models of speech signal recognition, to increase the probability of their recognition. The probability of recognizing speech signals and commands using the four-phoneme method is established, and it is shown that its application in practice with the help of the developed software allows to achieve a probability of 98%. The influence of amplitude and phase distortion of the speech signal on the recognition probability was studied, which showed that the recognition probability decreases when amplitude noise (recognition probability is 81.7%) and phase noise (recognition probability is 92.3%) are introduced into the speech signal. A comparative analysis of the four- and three-phoneme models is carried out, which shows that the recognition probability error of the four-phoneme model is 40% less than that of the three-phoneme model.

Analysis of traffic classification methods in software-defined networks

O.Y. Kulakov — 2025-08-23

This paper examines traffic classification methods in Software-Defined Networks (SDN). The purpose of this work is to analyze and systematize modern approaches to network traffic classification in the SDN environment.

Traditional classification methods, particularly port-based and Deep Packet Inspection (DPI), are analyzed. Machine learning methods, including SVM, Random Forest, neural networks, and clustering algorithms, along with their advantages and disadvantages, are investigated. The accuracy and efficiency of different classification methods are compared based on published research results.

The authors propose further research on the use of artificial intelligence algorithms in software-defined networks to improve traffic classification accuracy and adaptability to changes in the network environment. The results of comparing different traffic classification methods with a focus on their effectiveness in SDN networks are presented.

Analytical review of methods and technologies for real-time big data processing in IoT infrastructures

M.O. Kalashnyk — 2025-08-23

This paper presents an analytical review of modern methods and technologies for real-time big data processing in Internet of Things (IoT) infrastructures. It explores data stream sources, structural variability, and the key processing requirements such as latency, fault tolerance, and continuous availability. The advantages and limitations of Edge, Fog, and Cloud architectures are discussed, along with Lambda and Kappa approaches for building high-performance IoT systems. Special attention is given to stream processing platforms – Apache Kafka, Flink, Storm, and Spark Streaming – with an evaluation of their scalability, fault tolerance, and ease of deployment. The study highlights state-of-the-art anomaly detection methods in streaming data, including AutoEncoder, LSTM, and Isolation Forest, as well as the use of Complex Event Processing (CEP) for composite event analysis. Real-world applications in smart city systems, industrial automation, and healthcare are examined. The article summarizes current challenges and outlines directions for future research on improving security, adaptability, and efficiency in heterogeneous real-time IoT environments.

Analysis of modern approaches to cybersecurity requirements management during soft-ware implementation

S.O. Gnatyuk — 2025-08-23

This article examines modern approaches to managing cybersecurity requirements during software implementation. It analyzes the regulatory and legal framework, as well as scientific sources governing the requirements for the protection of information systems. Particular attention is paid to the classification of cybersecurity requirements (functional and non-functional), methods of their formulation, documentation, and integration into the software development process. It is determined that cybersecurity requirements management involves not only technical but also organizational and legal aspects, requiring a systematic approach. The role of policies, procedures, technical solutions, and regulations in forming a secure digital environment is considered. The importance of continuous monitoring, updating of requirements, and consideration of the dynamics of cyber threats is substantiated. Furthermore, best practices for managing cybersecurity requirements are presented, along with recommendations for improving the security level of information systems. The obtained results can be used to improve cybersecurity risk management practices, implement security standards, and develop secure software in both the public and private sectors.

Performance enhancement of RGB image convolution using convolution kernel clustering algorithm for ARM64 processor architecture

A.K. Shevchenko — 2025-06-01

The paper presents a method for improving the performance of RGB image convolution operation on the ARM64 platform using a convolution kernel element clustering algorithm. The proposed approach is based on vectorization of computations using NEON64 SIMD instructions and grouping of non-zero kernel elements with the same sign for efficient skipping of operations with zero elements. A mathematical model of vectorized convolution operation has been developed, which takes into account the specifics of sparse convolution kernel matrices. Experimental study on the Orange Pi 5 Pro platform demonstrated significant acceleration compared to the cv::filter2D() function of the OpenCV library: for medium-sized kernels (7×7 – 11×11), an acceleration of 5.0–9.7 times was achieved, for large kernels (12×12 – 15×15) – 1.7–5.5 times. The proposed method is particularly effective for processing high-resolution images and can be applied in real-time systems on single-board computers with limited computational resources.

Computerized planar tomography system for diagnostics of combat injuries

Y.V. Khobta — 2025-06-01

In this work, the use of mobile digital X-ray tomosynthesis complexes for diagnosis of shrapnel wounds in front-line hospitals was substantiated. During the research, an increase in the contrast of pathological images by 6...8 times was experimentally obtained in mobile X-ray complexes with tomographic information technology compared to X-ray images. A modeling stand was created in which a working sample of a veterinary mobile device with tomosynthesis was used and a measuring phantom was developed that simulates shrapnel lesions of the extremities. This made it possible to obtain reliable measurement results.

Package coding into ad-hoc networks

I.V. Teleshko — 2025-06-01

Based on the analysis of known approaches to coding network traffic in wireless data networks, an attempt has been made to substantiate the possibility and feasibility of using network coding in special-purpose networks (Ad-hoc networks). At the same time, the features of the implementation of some coding algorithms were considered from the point of view of the limitations caused by the environment of lossy networks. It has been shown that the implementation of packet coding methods in lossy networks, which are essentially Ad-hoc networks, is not only possible, but also useful in terms of increasing the reliability and efficiency of data transmission, but the answer to the question of how these methods work in practice requires additional implementation.

Security mechanisms for AODV and E-AODV protocols against black hole and gray tunnel attacks

S.O. Kudrenko — 2025-06-01

This paper investigates the security vulnerabilities of the AODV (Ad hoc On-Demand Distance Vector) and E-AODV (Enhanced AODV) routing protocols in mobile ad hoc networks (MANETs), focusing on two common attack types: black hole and gray tunnel attacks. A comprehensive analysis is conducted to examine how these attacks affect routing reliability, packet delivery, and network performance. E-AODV is evaluated as an improved protocol incorporating adaptive trust mechanisms, response timing analysis, and behavioral monitoring to mitigate malicious node interference. A simulation framework is implemented using a Python-based environment, where various network sizes (10–100 nodes) are tested. Key performance indicators such as Packet Delivery Ratio (PDR), End-to-End Delay, and Packet Loss Rate (PLR) are used to compare protocol behavior. Results show that E-AODV significantly enhances resilience to attack-induced disruption, outperforming standard AODV in both delivery efficiency and security reliability across diverse MANET topologies.

Problems and requirements when creating an automated heating system for residential premises with increased energy efficiency

I.Y. Sergeyev — 2025-06-01

The article discusses in detail the problems and requirements for creating an automated residential heating system with increased energy efficiency and explores the transformational potential of such automated systems.

The discussion begins with an overview of the importance of residential heating systems, emphasizing the need for increased energy efficiency in the face of environmental concerns and rising energy costs. The introduction of automated systems is introduced as a promising solution, leveraging advanced technologies such as smart sensors, machine learning algorithms, and IoT connectivity.

The article delves into the challenges posed by traditional heating methods, including common inefficiencies and environmental impacts, paving the way for a comprehensive understanding of the advantages offered by automated systems. Additionally, the article emphasizes the role of government incentives and rebates in promoting energy-efficient home upgrades, providing practical tips for homeowners considering the adoption of automated heating systems. The exploration of emerging technologies, advancements in energy efficiency, and the integration of artificial intelligence offers a glimpse into the future of residential heating.

In conclusion, the article underscores the benefits of automated heating systems, encourages homeowners to embrace energy-efficient solutions, and provides insights into the evolving landscape of residential heating systems. The adoption of these technologies is presented not only as a means of improving personal comfort and reducing energy bills but also as a critical step towards building a more sustainable and environmentally conscious future.

Modular multiplication on invariable number with group processing of multiplier bits and Montgomery reduction

V.L. Selivanov — 2025-06-01

Developed and studied a method for accelerating the computational implementation of modular multiplication by a constant number as a component of modular exponentiation from high bits – the basic computational operation of asymmetric cryptography. The acceleration is achieved by using precomputations to combine group processing of k bits of the multiplier and the corresponding Montgomery reduction. Numerical examples are given to illustrate the work of the proposed method.

It has been theoretically proved and experimentally confirmed that the developed method allows accelerating modular multiplication by a constant number by a factor of k in comparison with known methods.

Method for reconfiguring a distributed information system after partial physical destruction

A.S. Savchenko — 2025-06-01

The article addresses the problem of restoring the functionality of distributed information systems (DIS) that have suffered partial physical destruction and proposes a method for their reconfiguration. In cases of physical damage caused by external or internal factors, ensuring the continued operation of such systems is of critical importance. The loss of connectivity between elements can lead to decreased computational efficiency, disruption of data exchange, and partial or complete loss of system control.

The proposed method aims to restore connectivity and adapt the DIS to new operating conditions by reconfiguring its structure. The core idea of the approach is to identify alternative communication routes between system elements to compensate for lost connections. The method is based on modeling the system structure as an undirected graph, where damaged connections are represented as missing edges, and functionality is restored by constructing a set of finite simple chains.

The relevance of this research is driven by the increasing dependence on distributed computing systems in critical sectors such as military, energy, transportation, and telecommunications. Efficient recovery of their functionality minimizes the impact of destruction, enhances resilience, and ensures operational continuity even in crisis situations. The proposed method is universal and can be adapted to a wide range of distributed systems, including both computer networks and other complex cyber-physical systems.

The scientific novelty of the method lies in its ability to perform a comprehensive search for all possible connectivity restoration paths while minimizing computational costs. This is achieved by pre-narrowing the solution space, allowing the method to efficiently scale for systems with a large number of nodes. An additional advantage is its applicability for modeling system fault tolerance scenarios and predicting the consequences of destruction, making it valuable for cybersecurity strategy development and emergency response planning.

Intelligent agents in the fight against global threats

D.V. Nevinskyi — 2025-06-12

This paper explores the application of intelligent agents in combating tuberculosis, which remains a significant public health threat. A cellular automata-based disease spread model is proposed, enabling the analysis of infection dynamics while considering socio-economic and demographic factors. Simulations conducted for Lviv and Stockholm reveal significant differences in the speed of disease transmission depending on the initial level of latent infection.

In Lviv, the projected number of active tuberculosis cases reaches 308 per 100,000 people within ten years, highlighting the need for effective control measures. In Stockholm, where the initial infection rate is much lower, the disease spreads gradually, driven by migration processes. Model validation using official WHO data confirmed its accuracy, allowing it to be used for epidemic forecasting and the development of disease control strategies.

The results emphasize the importance of early diagnosis, active case monitoring, and the consideration of migration processes in shaping preventive measures. The use of intelligent agents can significantly improve epidemic management and enhance the effectiveness of public health strategies.

Method of distributed calculation on multi-core processors exponential on Galois fields for cryptographic applications

O.P. Markovskyi — 2025-06-01

The organization of rapid parallel calculation of the exponential on Galois fields for cryptographic applications on multi-core processors is proposed.

The proposed approach to parallelization is based on the possibility of exponentiation a number to any degree of two on Galois fields by using precomputations over the same time. Two schemes of organization of parallel computing processes of exponentiation on Galois fields of were proposed. For both schemes, the procedures for calculating partial exponential on k processor cores are developed in detail and numerical examples that illustrate their work are given.

It has been theoretically proven and experimentally confirmed that proposed method of distributed exponentiation on Galoise fields on multi-core processors allows, due to the parallelization and use of precomputation, to reduce the calculation time by 2×k times.

Algorithm for orchestration of encrypted traffic in SDN networks

Y.O. Kulakov — 2025-06-01

The article addresses the issue of overload in Software-Defined Networks (SDN) under increasing volumes of encrypted traffic, which complicates its classification and reduces the efficiency of traditional load balancing methods. The proposed algorithm performs preliminary traffic classification using DPI, NBAR, and Cisco AVC technologies, followed by the application of restriction policies for non-priority flows. The solution is based on the M/M/1/K queueing model and considers the characteristics of priority traffic. The proposed approach improves network fault tolerance, enhances the quality of service for critical applications, and reduces data loss in high-load environments.

Method of traffic orchestration in software defined networks considering quality of service parameters

Y.O. Kulakov — 2025-06-12

This study is dedicated to the method of traffic load balancing in computer networks using SDN technology. The path selection criterion is proposed that enables more balanced loading of data transmission channels while ensuring compliance with specified QoS parameters.

The modified method of traffic orchestration is proposed to reduce the time required to form a set of partially overlapping paths and to simplify the traffic balancing procedure. The availability of this path set enables the replacement of the rerouting process with a path reconfiguration procedure during data transmission.

The problem of information protection in electronic document management systems of medical organizations

V.A. Gasimov — 2025-06-01

The article is devoted to the study and processing of methods for creating electronic document management systems of medical organizations, increasing the level of protection of documents and information stored and processed in this system. For this purpose, International and local experience in the field of legislation on the protection of documents containing personal and medical information of patients in medical organizations was commented in the article, the issue of creating a distributed structured electronic document management system for medical organizations was considered, various protection methods were used to ensure the confidentiality of personal and medical information of patients, it was proposed to use the authentication procedure and secure encryption methods.

Performance analysis of parking occupancy prediction models in an IoT-based intelligent system

A.D. Dmytryshyn — 2025-06-01

The article investigates the effectiveness of parking occupancy forecasting models within an Internet of Things (IoT) intelligent system operating on cloud computing principles. The relevance of parking space management in modern urbanization is considered. The architecture of an analytical system is presented, which includes IoT sensors for data collection, a cloud platform for data processing and storage, and a forecasting module. Three time-series forecasting models are described in detail: LSTM (Long Short-Term Memory), Prophet, and SARIMA (Seasonal Autoregressive Integrated Moving Average). An experimental study of these models was conducted on a parking occupancy dataset, including their training, testing, and evaluation using MAE, RMSE, and MAPE metrics. A comparative analysis of the accuracy of the models was performed, identifying the advantages and disadvantages of each in the context of forecasting parking zone occupancy. The research results demonstrate the potential of using machine learning models to optimize urban parking infrastructure management and can be used for further improvement of intelligent transport systems.

Use of complementary filter for identification of motion parameters of elements of spherical parallel mechanism

A.O. Derkachenko — 2025-06-12

The article proposes to use a complementary filter in the SPM control system for processing data from the accelerometer and gyroscope. A complementary filter combines data from an accelerometer that measures linear acceleration, which can be used to determine the angle of inclination in a static position, and a gyroscope, which measures angular velocity, which is used to integrate and determine the angle of rotation. The filter calculates a weighted average of these two measurements, with the weights chosen to minimize the effects of noise and drift from each sensor.

An algorithm for calculating the angle of inclination of the SPM platform was developed, where the final value of the angle of inclination is the sum of the integrated value of the gyroscope and the instantaneous value of the accelerometer. At each stage of integration, the integral of the angle of inclination is corrected using the readings of the accelerometer. An experimental verification of the effectiveness of the complementary filter was performed to identify the motion parameters of the elements of the spherical parallel mechanism.

Analytical review of actuators and adaptive control in bionic upper limb prostheses

A.V. Avagyan — 2025-06-01

The article considers modern types of actuators used in bionic upper limb prostheses, with an emphasis on their classification, technical characteristics, advantages and limitations. A comparative analysis of pneumatic, hydraulic, electric, as well as innovative electromechanical actuators based on smart materials is carried out. Special attention is paid to actuator control systems: from classical methods, in particular PID controllers, to modern approaches using neural networks, machine learning and adaptive algorithms. The human-prosthesis interfaces and the challenges associated with noise in biological signals and the need for individual adaptation of the control system to the user are considered. The material is of practical importance for engineers and researchers involved in the development of a new generation bionic prostheses.

Hybrid models for detecting shadowburst anomaly in industrial IoT traffic

V.V. Alkema — 2025-06-12

The increasing deployment of Industrial Internet of Things (IIoT) systems within Industry 4.0 environments has introduced new cyber-physical vulnerabilities, particularly in the form of stealthy and short-lived anomalies that evade traditional detection mechanisms. This paper introduces and formalizes a novel anomaly type, referred to as ShadowBurst, which consists of protocol-conformant, high-frequency microbursts embedded in otherwise stable traffic streams. We propose a hybrid detection architecture that integrates Kalman filtering for temporal state estimation with machine learning techniques, specifically Isolation Forest, for residual-based outlier detection. The detection function is further enhanced by incorporating statistical scoring and behavioral profiling to improve anomaly visibility. Simulation results confirm that this hybrid Kalman–ML approach enables effective identification of ShadowBurst anomalies in time-sensitive IIoT traffic, addressing gaps left by signature-based and purely statistical models. The proposed model demonstrates high responsiveness to low-duration, protocol-mimicking threats and supports real-time deployment in smart manufacturing environments.

An approach to optimizing the microservices deployment model in a highly loaded environment

Y.B. Artamonov — 2025-03-17

The article proposes the use of a LB-Diversity algorithm for deploying microservices to increase system stability and optimize resources in cloud architectures. Traditional microservice systems often face node failure issues and security vulnerabilities due to homogeneous deployment of identical service instances. The proposed approach addresses these issues by combining load balancing with deployment diversity, where different versions of microservices are distributed across multiple nodes. This strategy reduces the risks associated with a single point of failure and mitigates the impact of attacks targeting common vulnerabilities in containerized environments.

To analyze the experiments, our own coefficients for assessing load balancing and system fault tolerance were proposed, which confirmed the results of previous studies on the choice of the LB-Diversity algorithm compared to traditional deployment methods. The diversity of deployment approach effectively limits the damage from potential security breaches by ensuring that only a small portion of the system is affected. This model offers a practical solution for enterprises that require reliable microservice architectures with high availability and security in dynamic environments with limited resources.

A method for fast implementation of Fourier transform with secured use of cloud computing

O.V. Rusanova — 2025-03-15

The article proposes a method for fast implementation of the discrete Fourier trans-form (DFT) on a terminal microcontroller (TMC), which is based on additive masking of signals and is distinguished by the fact that it updates the mask by changing its bit layers, which allows to update the mask before processing each input signal. The basic procedures of the method are theoretically justified and described in detail. An analysis of the effec-tiveness of the proposed method of homomorphic encryption of signal readings from a real object was performed. It is shown that due to the use of a faster procedure for updating the mask by changing its bit layers, the level of protection of signal readings against attempts to illegally restore them in the cloud is significantly increased. This is achieved by changing the mask for each signal.

It is also shown that the proposed method can reduce the time of encryption and de-cryption by two times. The conducted experimental studies generally confirmed the results obtained by theoretical evaluation of efficiency.

Method for synthesis of fault-tolerant topologies with implicit clusters based on de Bruijn transformations in redundant numeral systems

O.O. Honcharenko — 2025-03-15

The work is devoted to the development of a method for synthesizing topologies based on de Bruijn transformations in redundant numeral systems, which allows synthesizing fault-tolerant topologies of a given order, including those with implicit clusters. A method for forming such clusters and a method for studying the survivability of topologies using dynamic determination of failure probability based on betweenness centrality are also developed.

The proposed comprehensive approach allows us to synthesize graphs that, on the one hand, contain less redundancy, and on the other hand, have higher survivability due to better use of the available redundancy, which allows us to increase fault tolerance with lower costs and ensure better efficiency.

Mathematical model of measuring details on a coordinate measuring machine

O.M. Bezvesilna — 2025-03-15

The paper explores the significance of measurement accuracy in coordinate measuring machines (CMM), highlighting their role in modern quality control processes. Key sources of measurement errors, including geometric, thermal, kinematic, and random factors, are analyzed. The study presents a novel approach for developing error correction algorithms aimed at enhancing measurement accuracy. The mathematical model developed considers the primary error sources and provides a structured framework for their correction. An algorithm for error correction is proposed, detailing the integration of systematic error adjustments into the measurement process. The algorithm is designed for real-time application, offering dynamic adaptability to varying operational conditions.

The implementation of the proposed algorithm in CMM software demonstrates significant improvements in measurement precision. Results of modeling validate its effectiveness across diverse conditions. The paper concludes by emphasizing the scientific contribution of the proposed methodology, which combines theoretical advancements with practical applications to enhance the accuracy of CMM measurements.

ReliefF functional selection for traffic anomalies detection

S.O. Kudrenko — 2025-03-13

This paper addresses the problem of network traffic anomaly detection using machine learning techniques and feature selection optimization. As modern computer networks become increasingly complex and data volumes grow, efficient threat detection requires fast and accurate traffic analysis algorithms. A major challenge lies in distinguishing normal network activity from potentially malicious attacks, which may be disguised as legitimate traffic.

The study explores the use of the ReliefF method for selecting key network traffic features and its impact on the performance of the Random Forest classification model. The focus is on optimizing feature selection to reduce computational costs and speed up training while preserving essential indicators of anomalous activity. Special attention is given to evaluating system performance under different feature selection scenarios, allowing for an optimal trade-off between accuracy and processing speed.

The proposed approach is designed for automated intrusion detection systems (IDS) operating in real-time, requiring rapid responses to potential threats such as DDoS attacks, port scanning, unauthorized access, and exploits. The research aims to enhance the efficiency of existing network traffic analysis methods and adapt feature selection algorithms for high-load network environments.

Routing method in wireless IoT networks with high device density

S.S. Chumachenko — 2025-03-13

This research is based on the assumption that in the immediate vicinity of the calculated coordinates are located transit nodes, which are located along a straight line connecting the initial and final nodes of the route. This assumption is valid for networks with a high density of nodes. For networks with a limited number of nodes, it is advisable to focus on solving the problem of determining the required number of nodes of the route based on the distances between them.

The proposed method reduces the use of network resources by selecting a near-optimal route, taking into account the influence of the transmission speed on the level of the useful signal power and interference from neighboring nodes on the route. For example, it allows you to increase the overall data transfer rate compared to the approach based on determining the shortest route based on the number of transit sections.

Research on the modernization of the data transmission standard ARINC629

T.V. Kholyavkina — 2025-03-13

As of 2024, due to its high reliability and efficient data transmission between various aircraft systems, enhancing flight safety and efficiency, the ARINC 629 digital data bus exchange standard is still used in various aircraft models: Boeing 777-200/300/ER/F, Boeing 787-8/9, Boeing 747-8, Airbus A350-900/1000, Airbus A380-800, Embraer E-190/E-195, Bombardier CRJ900/1000, and Sukhoi Superjet 100. The aircraft listed above utilize ARINC 629 for data transmission among different systems: Flight Management System (FMS), Engine Control System (ECS), Air Conditioning (AC), Lighting (L), and Communication (C). The article suggests replacing the signal transmission material with fiber optic technology. Indeed, there are upgrades to this standard in the form of ARINC 818 [11, 12]. However, the implementation of these standards tends to be more specialized and less flexible.

Improvement of the mathematical model of the routing table taking into account the psychophysiological mechanisms of the reaction of the computer network administrator

O.V. Tolstikova — 2025-03-13

The presented work considers the problem of optimizing the topological structure of the network. In this case, an improved logarithmic function of the administrative distance was used, which corresponds to the fundamental law of the analysis of “man-machine” systems – the Weber-Fechner law. The results of calculations and computer modeling indicate that the intuitive reactions of the computer network administrator to changes in the logarithm of the administrative distance are accelerated when applying the administrative distances of the Weber-Fechner law, an approximately 10...15 percent acceleration of the intuitive reactions of the network administrator to sudden excitations is observed, which gives an additional gain in reducing the delays of adaptation to route changes by approximately 2%-3%.

Challenges and requirements for developing a secure computer-integrated warehouse for aircraft components with enhanced data confidentiality

I.Y. Sergeyev — 2025-03-13

The article discusses in detail the challenges and requirements for developing a secure, computer-integrated warehouse for aviation components with an increased level of data confidentiality, comprehensively explores the concept of a computer-integrated warehouse for aviation components and emphasises the critical importance of enhanced security measures. The first section outlines the challenges faced by traditional warehouse systems in aviation, emphasizing the risks associated with manual tracking and management of aircraft components. It also highlights the growing significance of technology in optimizing warehouse operations. The subsequent section delves into recent advancements in computer-integrated warehousing, including the integration of IoT, automation, and robotics. Recognizing the sensitive nature of aircraft components, the article underscores the importance of increased securityThe article further explores data confidentiality measures, encompassing encryption, secure data transmission, access control, and authentication protocols. It advocates for the implementation of blockchain technology to enhance data integrity and compliance with industry-specific data protection regulations. The subsequent section outlines the multifaceted benefits of computer-integrated warehousing with heightened security. Through compelling case studies, the article showcases successful implementations of computer-integrated warehouses in the aviation industry, emphasizing their positive impact on security and data confidentiality. Potential challenges in implementation, balancing security measures with operational efficiency, and addressing workforce adaptation and training concerns are also examined. In conclusion, the article summarizes key points and underscores the crucial role of computer-integrated warehousing with heightened security in the aviation sector. It encourages further research and investment in advancing warehouse technologies for sustainable growth in the industry.

Modular exponentation method with protection against power analysis

O.V. Rusanova — 2025-03-13

The article proposes a method of modular exponentiation on terminal microcontrollers, which provides protection against recovery of secret operands by power analysis. The method is based on the separation in time of processing of the exponent code bits and correspondent modular multiplication operations by storing the operands necessary for multiplication in memory. This prevents the comparison of the modular multiplications detected from the power consumption diagram with the values of the secret exponent code bits. A formalized procedure for modular exponentiation is presented, the functionality of which is illustrated by an example. A method for selecting the procedure parameters is developed in view of microcontroller embedded memory limitations.

It has been theoretically and experimentally proved by the proposed method, which provides protection against both simple and differential analysis of the power analysis without affecting the time of calculating the modular exponent.

Modified model of noise filtering in images based on convulsive neural network with the addition of residual connections and attention module

V.Y. Mukhin — 2025-03-13

In numerous applied image processing tasks, ranging from technical diagnostics to medical imaging, the accurate restoration of images affected by severe salt-and-pepper (SAP) noise is of critical importance. This type of noise introduces isolated but highly intense white or black pixels, which can significantly distort the visual representation and complicate subsequent analysis.

This study presents a modification of the existing SeConvNet convolutional neural network, specifically designed to enhance SAP noise removal. The primary objective is to improve the processing of images with prominent white noise artifacts, where the original SeConvNet model has demonstrated suboptimal performance. The proposed modification incorporates a novel block that combines residual connections with both channel and spatial attention mechanisms (Channel+Spatial Attention). This integration, implemented through the Convolutional Block Attention Module (CBAM), enables the network to emphasize informative channels and critical spatial regions, thereby enhancing the suppression of high-contrast noise artifacts while preserving fine structural details.

Experimental results indicate a notable improvement in image restoration quality, particularly in datasets where noise-affected regions exhibited a high intensity of bright spots within a 5–8% range. The proposed approach was evaluated on MRI scans, confirming its efficacy in handling complex textures and domain-specific noise artifacts. The significance of these findings lies in the potential integration of the enhanced SeConvNet into medical diagnostic applications and other fields where the precise preservation of fine image structures is paramount.

Despite computational constraints, the introduced modifications have led to improved SAP noise suppression, underscoring the strong potential of this approach for further research and practical implementations.

Using fuzzy logic methods in precision part measurement on a coordinate measuring machine

V.Y. Larin — 2025-03-13

This article examines the application of fuzzy logic methods for correcting measurement errors on coordinate measuring machines. An adaptive correction algorithm is proposed, which significantly reduces systematic errors and improves the accuracy of precision part measurements. The algorithm is based on the use of fuzzy sets to model and compensate for errors arising during the measurement of complex geometric shapes. A detailed simulation of the algorithm’s performance has been conducted, confirming its effectiveness in reducing the mean measurement error and its dispersion. The proposed method can be integrated into the software of coordinate measuring machines for automatic correction of measurement results, ensuring improved accuracy without significant operator intervention. The obtained results can be applied in the aerospace, mechanical engineering, and other high-precision industries, where quality and accuracy in geometric parameter control are of utmost importance.

Improving measurement accuracy on coordinate measuring machines under destabilizing factors

L.V. Kolomiets — 2025-03-13

The paper develops theoretical foundations for improving measurement accuracy on coordinate measuring machines (CMM) through comprehensive consideration of destabilizing factors' influence. A generalized mathematical model based on fourth-rank tensor fields is proposed, which takes into account the mutual influence of thermal deformations, vibrations, mechanical stresses, changes in humidity, air pressure, and electromagnetic interference. A system of nonlinear integral equations for describing deformation fields and an error compensation algorithm based on nonlinear filtering methods have been developed. The possibility of improving measurement accuracy through the application of the developed model and results correction algorithm has been theoretically substantiated. A methodology for practical application of the proposed approach for various types of coordinate measuring machines and operating conditions is presented.

Mathematical model of trajectory planning for measuring precision spatial surfaces on a coordinate measuring machine

V.V. Kozlovskyi — 2025-03-13

The paper presents a novel approach to optimizing the probe tip trajectory of a coordinate measuring machine when inspecting complex spatial surfaces. A comprehensive mathematical model has been developed, incorporating B-spline trajectory representation, system dynamics modeling, and a stochastic measurement error model. A quality functional is proposed that accounts for surface geometric features, system dynamic characteristics, thermal deformations, and vibrational effects. A trajectory optimization algorithm based on sequential quadratic programming has been developed. The algorithm convergence and measurement uncertainty estimation methods are theoretically substantiated. Tensor analysis of local surface topology and a thermoelastic deformation model are presented. An adaptive measurement strategy with dynamic trajectory parameter correction is proposed.

Method of developing automated information support for integrated modular avionics systems: monitoring, diagnostics and reliability improvement

Y.B. Kovalenko — 2025-03-13

Advances in avionics technology have significantly increased the complexity of modern aircraft systems. Integrated modular avionics (IMA) plays a critical role in providing an efficient, reliable, and maintainable avionics architecture by consolidating multiple functions onto common computing resources. This paper presents a method for developing automated information support software for IMA, focusing on real-time monitoring, diagnostics, and state management of avionics modules. The proposed approach emphasizes automation of data collection and processing, which enables early fault detection, predictive maintenance, and rapid response to component failures or degradation. By integrating automated monitoring capabilities, aircraft operators can improve system reliability, minimize downtime, and optimize maintenance planning. This paper highlights key cybersecurity considerations, including protection from external threats, intrusion detection, and secure data transfer between IMA modules. As networked avionics systems become increasingly prevalent, implementing robust security measures is essential to prevent unauthorized access, data manipulation, or system failures that could jeopardize flight safety. Additionally, this study examines key aspects of system architecture design, emphasizing modularity, scalability, and compliance with industry standards such as ARINC 653 and DO-178C. The modular nature of IMA provides greater flexibility in system design, allowing new features to be integrated or existing modules to be upgraded without extensive reconfiguration. Compliance with aviation safety standards and software certification ensures that automated information support solutions meet regulatory requirements. Recommendations for improving diagnostic and monitoring algorithms are provided to optimize system performance. Advanced data analytics techniques, including machine learning and predictive analytics, are explored to improve fault detection accuracy and optimize maintenance schedules. Using real-time data analytics, operators can implement condition-based maintenance strategies, reducing unnecessary inspections while improving overall system reliability. The results of this study confirm that the integration of automated information support systems significantly improves the efficiency and reliability of IMA-based avionics. By implementing advanced monitoring and diagnostic capabilities, these systems contribute to increased aircraft availability, reduced maintenance costs, and improved flight safety. In addition, by ensuring compliance with modern aviation standards, such solutions align with industry best practices and regulatory requirements. In conclusion, the development and implementation of automated information support software for IMA represents an important step towards achieving higher levels of operational efficiency, reliability, and cybersecurity in modern aviation. As avionics systems continue to evolve, the integration of intelligent monitoring solutions will be essential to meet the growing demands of next-generation aircraft while ensuring compliance with stringent safety and certification standards.

Method of exponentiation on Galois fields for fast implementation of cryptographic protection in IOT

O.A. Verba — 2025-03-13

A new organization for the exponent on Galois fields computing is proposed for the rapid implementation of cryptographic mechanisms for protection against external interference in the operation of remote control systems based on IoT technologies. The contraction of computation time is achieved by combining two multiplicative operations on Galois fields: squaring and multiplication by a constant number with the use of recalculations. The mathematical justification of the proposed method and numerical examples illustrating its operation are given.

Theoretical and experimental estimates of the effectiveness of the proposed method for accelerating the implementation of exponentiation on Galois fields were obtained: it was shown that it allows reducing the time of the corresponding calculations by 4.5 times compared to known methods.

Exploratory data analysis and visualization on the example of an e-commerce enterprise

S.R. Suleimanova — 2024-11-04

This article presents an approach to exploratory data analysis and visualization using the example of an e-commerce company. The study examines key stages of exploratory data analysis, including data preprocessing, visualization, anomaly detection, correlation analysis, and cluster analysis, aimed at preparing data for solving machine learning tasks in future research. These tasks include estimating a time series model, identifying trends, seasonal and cyclical components of time series, customer clustering, new customer classification, and predicting the quantity of items sold within customer clusters. The proposed approach can be applied to the analysis of other e-commerce datasets.

Increasing the sensitivity of the sensor of the coordinate machine

O.V. Chalyi — 2024-11-04

The article investigates the sensitivity of the coordinate measuring machine sensor to external factors. Mathematical models have been developed for the evaluation and compensation of systematic and random errors arising from temperature changes and vibrations. A comprehensive model describing the sensor behavior in three-dimensional space, taking into account rotational errors, is presented. Methods for optimizing error compensation based on minimizing the root mean square error are proposed. The obtained results have practical significance for improving the accuracy of coordinate measurements in various industries.

Improving measurement accuracy of aviation parts on a coordinate measuring machine

S.F. Filonenko — 2024-11-04

This article is devoted to the development of methods for enhancing the accuracy of aviation parts measurements on coordinate measuring machines, which is critically important for ensuring quality and safety in aviation manufacturing. A mathematical model is proposed that accounts for the main types of errors: geometric, kinematic, and thermal. An automatic correction algorithm is also developed, allowing for the minimization of these errors' impact on measurement results. The application of this approach contributes to the improvement of accuracy and reliability in controlling geometric parameters, which is essential for the production of structurally complex and critical aviation components.

Method of synthesis of digital controller for UAV automatic control system

O.M. Tachinina — 2024-11-04

In this article the method for synthesizing a digital controller for an unmanned aerial vehicle (UAV) automatic control system is proposed. The suggested method is simple to use and enables rapid parametric tuning of the digital controller for a specific loop of the UAV automatic control system. The synthesized digital controller can be integrated into the software or hardware of the UAV automatic control system. The proposed method can be used to design digital controllers for automatic control systems of any type of UAV.

The method of adaptive K-path routing in special purpose wireless networks

A.A. Skrypnychenko — 2024-11-04

The task of ensuring the end-to-end quality of service of heterogeneous wireless networks (HWNs) with random multiple access is considered. The processes of the emergence of conflicts between the universality and complexity of route selection and resource allocation in BPM are analyzed. A technique for eliminating conflicts between fairness and optimality of resource allocation with different numbers K of routes has been developed. It is shown that with a rational choice of the number of routes, depending on the state and parameters of the autonomous segments and the network as a whole, the functions of each level and, accordingly, the information parameters of the traffic at this level can be attributed to one of two alternative groups: functions that depend on a specific technical implementation networks or application-oriented functions. Accordingly, a global approach to the optimal selection of a radio access technology (RAT) to each of the routes included in the set K is formulated, and an approach to RAT selection using a distributed adaptive search algorithm based on the peak rate at which users are able to receive and transmit is proposed traffic flows. The advantage of the adaptive K-path routing method compared to the classical method was estimated by means of calculations and computer simulations. A distributed system for choosing the number of routes has been developed based on the optimization of the set of routes with the elimination of redundancy.

Method of modular multiplication by invariable number for open key cryptography quick implementation in IoT

V.L. Selivanov — 2024-11-04

The article proposes a method of accelerating the operation of modular multiplication important for cryptographic applications due to use of precomputations. The technology for forming a table of precomputations, whose depend on a invariable multiplier and modulus, has been developed in detail. A formalized description of the proposed procedure for accelerated modular multiplication using precomputations is given. The statement is illustrated by a numerical example. It has been theoretically proven and experimentally confirmed that by using preccomputations according to the proposed method, the implementation of this operation is accelerated by four times. At the same time, the execution time of the basic operation of public-key cryptography – modular exponentiation – is reduced by 1.6 times.

Modernization of flight information reading and processing means

A.S. Savchenko — 2024-11-04

In modern conditions, the task of quickly transferring primary data directly from the on-board recorder of the aircraft to a solid-state information carrier for further processing arises. The article proposes the modernization of flight information reading and processing complexes using the developed prototype of the hardware and software part of the BIF-4T interface block and its own software. This will contribute to increasing the efficiency and comfort of the work of aircraft maintenance specialists, as well as saving time resources and reducing the human factor.

Technology of analyzing electronic media to identify informational and psychological influence

M.O. Riabyi — 2024-11-04

Our many years of research into media information flows have allowed us to reveal a general scheme for implementing informational and psychological influence. The structures created by the decision-making centers (DMCs – “Kremlin towers”) of the aggressor during the hybrid war are designed to conduct information and special informational-psychological operations (SIPO) that support military actions through acts of informational-psychological influence. These operations are implemented by publishing “toxic” messages in news media controlled by the aggressor. The content of these messages poses an informational threat. These messages are then spread further by the aggressor’s network of “bot farms” on social media, simulating public opinion. During wartime, SIPO aim to exhaust society, undermine the morale of the military, and prompt ill-considered military-political decisions by state authorities. Together, structured messages and topics form an “information matrix” that characterizes the information content of individual IPI in the process of conducting hybrid SIPO. The work is devoted to the further development of models and methods of detection and assessment of PR influence to identify and establish the informational content of informational and psychological influence. The refined technology is formulated in an analytical form. The main elements necessary for its practical implementation are identified. The technological process of analyzing electronic media to identify and establish the information content of IPI is described using a UML usage diagram. An example of fragments of an automatically generated report, built using the analyst's AW software, is provided, which form the basis of the final analytical report, and the analyst's conclusion on narratives and identified IPI for the reporting period in the form of abstracts.