The article presents an analysis of concurrent execution issues and delivered performance in large-scale distributed applications deployed in cloud-native environments. The relevance of this direction is driven by the accelerated diffusion of the microservice paradigm and container-orchestration practices, within which classical synchronization and coordination approaches often become the dominant factor behind throughput degradation and latency growth. The text identifies baseline patterns of state management and state processing and then examines–at a detailed level–the causes and enabling conditions of data races in asynchronous execution loops. A separate emphasis is placed on the specificity of Kubernetes operators and on the requirement of idempotent reconciliation cycles as a key prerequisite for predictable system behavior under repeated triggers, partial failures, and mismatches between the observed and desired state. The research goal is formulated as the development of recommendations aimed at reducing latency and increasing reliability under concurrent access to shared resources and shared entities. To achieve this goal, methods of systems analysis are applied, architectural-pattern modeling is performed, and retrospective reflection on recurring failure patterns observed in production systems. The theoretical foundation relies on works devoted to distributed ledgers, while the applied part is supported by operational guidelines and engineering practices for running NoSQL solutions. The outcome is a description of the distinctive properties of a model for handling concurrent requests, designed to improve the resilience and controllability of distributed-component behavior. The findings presented in this work are expected to be of practical interest to system architects, DevOps engineers, and researchers working in the field of distributed computing.
The article examines the theoretical foundations for selecting algorithms and data structures to ensure secure storage and processing of metadata in IoT systems using the Ethereum blockchain. A classification of metadata types specific to heterogeneous IoT environments is presented, taking into account semantic significance, update frequency, and data criticality. Formal requirements for algorithms are formulated, covering resistance to forgery, computational complexity, scalability under high-intensity request loads, and resource efficiency in terms of gas costs and network throughput. A comparative analysis of data structures employed in the Ethereum infrastructure, including Merkle Tree, Merkle-Patricia Trie (MPT), Multi-State MPT, and GPU-accelerated modifications, is performed according to criteria such as asymptotic complexity, memory efficiency, and suitability for incremental updates. A conceptual model for organizing metadata exchange between IoT nodes and smart contracts is proposed, incorporating modules for encoding, verification, gas cost optimization, and standardized interaction interfaces. The presented results provide a theoretical basis for developing formally verified and energy-efficient solutions in the field of secure Ethereum blockchain integration with the Internet of Things.
Oleg Kravets, Ali Husein, Diana Getmanskaia, Mustafa Al-Imari · 7 authors
The article discussed an automata model of the functioning process of a system with distributed ledger technology based on a blockchain. The goal is to develop a special mathematical system with a distributed ledger based on a blockchain, taking into account the specifics of implementing algorithms for mutual information coordination, the possibility of combining individual nodes into groups, and implementing alternative strategies based on the development of appropriate models and algorithms that ensure increased stability in their operation. Automata theory was used, theory and methods of mutual coordination were applied, and the mechanism of the functioning process of a system with a distributed register was implemented. An automata model has been obtained and investigated. Thus, an automata model of the distributed ledger technology blockchain system node functioning process has been developed, which differs from the node representation by a finite state machine with a variable structure and a linear tactic with the possibility of implementing non-standard functions: the formation of a branch of processed data and a temporary blockage attack, and provides for obtaining the dependence of the sequence of changing the node's behaviour strategy options on the conditions of the environment it interacts with.
The problem of reproducibility of experiments in optimizing validator allocation in blockchain networks with Proof of Stake consensus was investigated, in particular due to the absence of standardized datasets and unified testing methods, which complicates the objective comparison of algorithms. To tackle this issue, we propose a method for building test datasets that rely on deterministic pseudorandom sequence generators and validator profiles calibrated against Ethereum network statistics. Each validator is described by a set of parameters that includes the stake size with the minimum requirement according to Ethereum standards, performance with a uniform distribution, reliability in a high range, network delays depending on the geographical proximity of participants, geographical location according to the actual statistics of validator distribution by regions, quality of network connection, and slashing history according to the violation statistics in the Beacon Chain. Three datasets of different scales were created for small, medium, and large network configurations with fixed initial values of the generators to ensure full reproducibility of experiments. A multi-criteria evaluation system was developed based on a generalized quality indicator that maximizes system throughput and minimizes load imbalance and network delays with scientifically grounded weighting coefficients. The tenfold testing protocol ensures the statistical reliability of results and reduces the impact of randomness on conclusions. The experiments conducted a comparative analysis of four allocation algorithms: a hybrid metaheuristic method based on particle swarm optimization with local search, random allocation with correction, an adapted Ethereum shuffling mechanism, and a greedy algorithm. The experimental results revealed scale-dependent efficiency of the algorithms: the hybrid method provides high optimization quality at all investigated scales, but quadratic growth of execution time limits its application to periodic offline planning of network configuration; the shuffling mechanism demonstrates stable medium-quality results with fast execution; the random method is characterized by moderate speed with variable results; the greedy algorithm shows maximum speed with deterministic results but variable efficiency depending on the network scale. The proposed method forms a basis for standardizing experimental research in Proof of Stake consensus systems. It ensures the objective comparison of new algorithmic solutions for validator allocation in decentralized blockchain networks.
Open access
Advanced Research in Systems and Signal Processing
Andrey Zaytsev, Nikolay Dmitriev, Evgenii Konnikov
A unified software-analytical suite is proposed. It implements a closed-loop control cycle for regional energy systems. The implementation combines event-driven modeling with two-stage stochastic optimization. The suite includes adaptive web parsers. The parsers extract and semantically verify telemetry data regardless of changes in web page structures and anti-bot mechanisms. The system employs the discrete-event simulator SimPy. That simulator reproduces equipment failures, load fluctuations and external disturbances. An analytical subsystem processes textual event logs. It applies TF-IDF and cosine similarity. It simulates quantum annealing to determine automatically the optimal cluster count. It evaluates cluster stability. A Pyomo-based optimization module solves a two-stage optimization program. Scenario generation employs Monte Carlo and Latin-Hypercube sampling. Subtasks distribute across computing resources in parallel. The system provides scalable configuration. It ensures high availability and fault tolerance. The solution offers extensible visualization. It supports flexible parameterization and API integration. Testing on real operational data for a regional energy system confirmed adaptability of the suite. It also demonstrated capacity to scale when the number of nodes and the volume of events increases. Future work will integrate machine learning algorithms for predictive analytics. The plan includes extending the model to multistage problems with distributed ledger technologies.
Jan 1, 2025·VI All-Russian (National) Scientific Conference "Science, Technology, Society: Ecological Engineering for Sustainable Development of Territories"
A mathematical approach is proposed for evaluating the resilience of a distributed ledger of SmartDust-class sensor microsystems under conditions of cyber-physical attacks and industrial interference. A stochastic model of the trusted sensor network is developed, incorporating the probabilities of node compromise, telemetry packet loss, and data verification errors. Analytical expressions are derived for the indicators of data trustworthiness, latency, and energy reliability of the system. The simulation results demonstrate the influence of network topology parameters and attack intensity on the integral resilience index of the sensor infrastructure.
Bitcoin, which was launched in 2009, is one of the most popular blockchains. To sustain and secure the system, enough mining power must be needed. However, various factors can encourage miners to leave the Bitcoin network. This risk should be assessed in advance by introducing metrics to detect hash rate changes. For this purpose, this paper proposes a statistical method to determine whether there is a significant difference in computational power for the two given periods. Our proposal consists of three hypothesis tests that consider Bitcoin difficulty adjustments. The first and second tests detect hash rate changes in the mining resources across the Bitcoin network. The third focuses on shifts in the distribution of mining power among different pools. We conducted simulations to elucidate the statistical properties of the detection power of the first and second methods. In addition, we apply our three statistical tests to the Bitcoin block data at height 756,000 through 836,640 (from September 28, 2022 to March 28, 2024). Based on the inference results, we discuss how the mining power had fluctuated by some intervention effects, such as the drop in the Bitcoin price. This provides insights to understand and evaluate the stability of Bitcoin.
This paper aims to discuss the function of software in satellite system and the reliability analysis of satellite software. Firstly, the overview of satellite system and the importance of software in it are introduced. Then, the concept of reliability, reliability evaluation method and factors affecting reliability of satellite software are expounded in detail. Then, the strategy to improve the reliability of satellite software is discussed. Finally, the article looks forward to the future development trend of satellite software reliability, including the application of artificial intelligence, machine learning, and distributed ledger technology. These new technologies are expected to further improve the reliability of satellite pieces and provide a solid guarantee for the safety of satellite communication.
Currently, the relevance of using crypto assets is growing rapidly. In recent years, cryptocurrencytrading has become one of the most discussed topics in the world of finance and investment.Cryptocurrencies such as Bitcoin, Ethereum, attract the attention of millions of people due to their innovativeness,high profit potential, and decentralization possibilities. The blockchain technology, on whichcryptocurrencies are based, is one of the most innovative and promising technologies in the market. Studyingcryptocurrency trading helps understand how private investors and companies can use blockchaintechnologies for investment and business development. One of the main reasons for the popularity ofcryptocurrency trading is its high level of volatility. The cryptocurrency exchange rate can change quickly,providing opportunities for profit. This article focuses on exploring the use of predictive analytics fordecision-making in decentralized systems using cryptocurrency trading on centralized and decentralizedexchanges as an example. The research conducted in this work aims to investigate decentralized and centralizedsystems to further develop decision support systems. A general description and operation schemesof decentralized and centralized dynamic systems are provided using cryptocurrency exchanges as a researchexample. This scientific article examines the typical structure of centralized and decentralizedcryptocurrency exchanges, analyzing the fundamental components and principles of their functioning.The article discusses the internal organization of the exchange, including the system for storing digital assets, transaction execution mechanisms, security provisions, and risk management. It also examines theinteraction between the exchange and market participants, as well as regulatory bodies. Furthermore, thisscientific article explores the rules and principles of operation for traders and market makers on centralizedand decentralized cryptocurrency exchanges. It covers the main strategies and tactics used by marketparticipants to ensure liquidity and optimize trading operations. The article compares the trading approacheson different types of cryptocurrency exchanges considering their specific features and impact oncryptocurrency price dynamics. The presented results can contribute to a deeper understanding ofcryptocurrency trading processes and optimize decision-making strategies for investors and traders in thecrypto asset market.
The primary trend in the development of modern information technologies is the migration of computations to the cloud, making distributed computing the dominant strategy for information processing. In particular, this poses the challenge of reliable distributed data storage. A well-known approach to solving the problem of distributed data storage is blockchain or, more generally, distributed ledger technology. A key challenge of this technology is creating an effective mechanism for the global numbering of registry records. The complexity of solving this problem results from the fundamental limitations of distributed computing — the inability to accurately synchronize distributed computing processes and the limitations resulting from the CAP theorem for distributed data stores. The authors attempt to circumvent the mentioned limitations based on the hypothesis that such limitations can be overcome by considering both the network topology and narrowing the class of distributed systems to distributed registers. The work is based on methods of modeling distributed computing, particularly the model of space-time diagrams proposed by L. Lamport. This model allows us to introduce such a tool as logical clocks, including Lamport's logical clock algorithm. Unfortunately, Lamport's logical clock algorithm allows assigning a common timestamp to different events if they are concurrent. The paper proposes an algorithm that is a composition of Lamport's clock algorithm and the wave algorithm, which is not only a logical clock but also assigns different timestamps to different events. Thus, this algorithm provides a mechanism for the global numbering of entries of distributed ledger replicas. A problematic issue remains gaps in the series of ledger entry numbers. Thus, the paper proposes an effective mechanism for the global numbering of records of a distributed register and identifies a shortcoming of this mechanism. Further study is to identify specific conditions in terms of network topology that would ensure the absence of the mentioned shortcoming.
Abstract— The paper presents the results of an analysis of the decrease in cryptographic strength of the most common symmetric ciphers, taking into account the development of cryptanalytic methods. The vector of the threat to the reduction of information confidentiality stored and processed in information systems in the long term has been determined. An approach to constructing hybrid ciphers, based on the symbiosis of a composite cipher and the Vernam cipher, has been proposed to enhance the asymptotic cryptographic strength of symmetric cryptographic systems used for data encryption in information systems, the relevance of stored and processed information in which does not significantly decrease over time. For instance, this is applicable to information systems built on distributed ledger technology (blockchain networks).
The problem of monitoring a computer network under conditions of limitations on the use of system resources and high requirements for the survivability of the monitoring system has been considered. An autonomous decentralized computer network monitoring system has been developed, consisting of a team of software agents. Each agent can operate in two modes: main mode and monitoring system management console mode. In the main mode, the agent collects information about the computer network. In management console mode, the agent provides the user with access to information collected by all agents and allows the user to execute commands to manage the monitoring system. The developed monitoring system allows you to obtain more reliable information about the operation of the network with greater efficiency under the conditions of limitations on the use of system resources specified by the user. The autonomous monitoring system is created on the basis of the concept of multi-agent systems, within which a software agent of the system has some initiative for planning and implementing monitoring scenarios. The operation of software agents implements methods for organizing adaptive processes for collecting information using the principles of self-organization and the concept of structural adaptation. A decentralized software architecture for an autonomous monitoring system without a control center has been proposed. This ensures high reliability and survivability of the monitoring system. The software architecture of the autonomous monitoring system implements the SMA application software interface and the corresponding software library, which allows you to collect statistical data on the operation of the computer network and its nodes. The implementation of a software agent and a management console for an autonomous computer network monitoring system has been considered. Key words: computer network monitoring, autonomous system, decentralized control, software agent
Open access
Cybersecurity and Information Systems
Advanced Data Processing Techniques
Advanced Research in Systems and Signal Processing
This article examines directions and mechanisms for increasing data reliability in computer networks. Currently, the rapid development of information technologies, the rapid growth of data flow, high-quality data processing carried out in network technologies, and the increase in the volume of data lead to an increase in the problem of data reliability. It is an urgent issue to find solutions based on the use of modern technologies to solve these problems. The simultaneous processing of various types of data in information systems, video, audio, text and digital data, creates big data. The variety of data types in bigdata creates the problem of quality data processing, which greatly affects the reliability of the data. Research shows that breaches of data integrity mainly manifest in three directions. In this case, there is a violation of the reliability of interrelated data in data transmission and storage, in the processing of large volumes of data and in the transcription of video data. It is created due to errors created during data transmission based on artificial and natural redundancy. To solve the mentioned problems , increasing data reliability based on blockchain mechanisms for payment systems in data transmission, increasing data reliability based on error minimization mechanisms in video information systems, and distributed computing and parallel mechanisms in large-scale information systems based on methods of increasing data reliability are researched.
The paper considers the problems associated with the organization of the computing processin monitoring systems with mobile components based on a distributed ledger (DL), including thetask of redistributing the computing load. The requirements for the functioning of modern distributedmonitoring systems include the coordinated operation of nodes of the entire system belongingto various layers of the computing environment, including foggy and edge layers, which are highlydynamic. The joint use of DL technologies and mobile components as part of distributed monitoringsystems makes it possible to expand the range of tasks solved by such systems, including due tothe fact that it removes issues related to the synchronization of geographically distributed copiesof data. However, with such an organization of a distributed system, it is necessary to take into account the following features of the computing environment: latency associated with data synchronizationat DL nodes, changes in the geographical location of mobile components, limitedonboard energy resources and high dynamism of the fog and edge layers. Previous studies haveshown that in highly dynamic computing environments, the use of the search space reductionmethod based on ontological analysis is effective. For the correct operation of this method, it isnecessary to develop an ontological model reflecting the features of the considered computing andcommunication environment, including DL and mobile components. In this paper a new ontologicalmodel of the functioning of a distributed monitoring system has been developed, taking intoaccount the presence of mobile components and DL nodes. Production rules for placing computationalload in foggy and edge layers have been developed and a software model has been implementedbased on them, which allowed a number of computational experiments to be carried out.The results of experimental studies have demonstrated the effectiveness of the proposed approachand the adequacy of the developed ontological model.
Evgeny A. Titenko, I. E. Chernetskaya, L.A. Lisitsyn, М. А. Titenko · 5 authors
The article describes approaches and methods for managing a group of moving objects,characterized by the ability to autonomously make decisions about their status within the group.Another problem of managing such a grouping is weak predictive solutions for the connectivity ofpairs of elements and their dependence on a single control center. Nanosatellites operating underconditions of uncertainty in the internal and external environment are considered as such objects.The goal is to ensure the coherence of the group’s apparatus through a decentralized change instructure. It is shown that methods and algorithms for dynamic reconfiguration of a group of movingobjects predominantly use a centralized approach and a single ground control center, which isimpractical for small space exploration. A class of management methods using knowledge processingmethods and technology (artificial intelligence technology) is considered, allowing for theidentification and use of additional information about the configuration of the group. Configurationis understood as a dual system that describes the composition and connections between neighboring elements with some quantitative assessment. The article checks the connectivity configurationof elements to ensure continuous data transfer between a pair of arbitrary groupingelements. The proposed reconfiguration method is hierarchical: at the upper level, reconfigurationis based on the principles of self-organization; at the lower level, the grouping is understood as anadaptive system that changes its state based on a trained neural network based on historical data -time series of parameters of devices and their locations. The method is a two-level cycle of pollingeach element for grouping its neighbors and drawing up a network map. This network map showsthe available connections, taking into account the current steam numbers of each device. The second(nested) polling cycle uses control information about the future state of the device and theconnectivity of the group as a whole. Making changes to the network map instances by each deviceand updating the network map instances allows, upon completion of the polling cycles, to obtainthe configuration of working devices. The results of the comparative analysis showed that managementmethods based on the principles of self-organization and adaptive change in structure arethe most suitable for dynamic reconfiguration of the group. This result is possible due to the supportof forecasting steps.
The implementation of a framework for a fixed deposit system using smart contract in Remix IDE provides a secure and efficient method for managing fixed deposit accounts. This system utilizes the Ethereum blockchain, which ensures transparency, security, and immutability of data. The Smart Contract is coded using the Solidity programming language and designed using the Remix Integrated Development Environment. The framework allows for the creation of new fixed deposit accounts, depositing funds, and withdrawing the funds. Additionally, the system implements interest calculations and provides notifications to the account owners. This framework provides a reliable and automated fixed deposit system, improving the functionality of financial institutions.
Blockchain technology has received a lot of attention recently due to its potential to create decentralized and secure data systems. This technology is a digital ledger technology that is tamper-evident and tamper-resistant, offering a new way of storing and sharing data. In this review, the author will summarize the present state of research on blockchain technology, including its applications and benefits, as well as potential pitfalls. The author will review the latest research on blockchain technology in different domain areas, comparatively finance, healthcare, and supply chain management, and provide insights into the future direction of this technology. The main functions of security deposits, such as the financial management system, computerized order entry system, and information interchange, have received a lot of attention in many pieces of literature. In this research paper, the author reviews the existing research papers and applications available for the security deposit using blockchain technology. The goal of this research paper is to give readers a thorough grasp of the state of blockchain technology research today and how it might affect a variety of fields.
We consider ways to improve the performance of zero-knowledge succinct noninteractive argument of knowledge (zk-SNARK) based on polynomial sets, such as quadratic arithmetic programs (QAP), square arithmetic programs (SAP), quadratic span programs (QSP), square span programs (SSP), quadratic polynomial programs (QPP), etc. To improve the performance of zk-SNARK, batch data processing methods, various modifications of exponentiation problems, bilinear pairings based on elliptic curves, etc. are used. A comparative analysis of the complexity of the common reference strings formation, the construction and verification of the calculations reliability proofs, as well as the sizes of common reference strings and proofs has been carried out.
On February 24, 2022, Russian forces began their invasion of Ukraine. As of May 2023, approximately 20% of Ukraine has been occupied by Russia, and the war is still ongoing. Conflicts and wars devastate many buildings, infrastructure, regional transportation networks, and telecommunications networks. The outbreak of war threatens the very existence of not only the occupied territories but also the nation itself. Obviously, this has a major impact on the continuity of social life itself.On January 30, 2020, the World Health Organization declared COVID-19 a Public Health Emergency of International Concern. This declaration remained in effect until its termination on May 5, 2023. During this period, the pandemic caused global logistical outages and disrupted human interaction. The outbreak of infection caused by the pandemic restricted the ability of people to meet or talk directly with each other.Extreme weather events caused by climate change are becoming more frequent and more damaging every year. In July 2022, temperatures exceeding 40°C were observed in eastern England for the first time in recorded history. Abnormally high temperatures caused by heat waves lead to major fires in the region. The largest wildfire in southwestern France burned more than 19,000 hectares of land. It is reported that more than 34,000 residents were evacuated.Whatever the cause, natural disasters or conflicts, they generally have a significant impact on the lives of citizens and social activities. The impacts are long-lasting. Depending on the type of disaster, the disaster recovery frameworks that have been effective in the past may not work in some situations.In the field of higher education, such as university education, the use of learning analysis, which aims to clarify learners' learning behavior based on their learning history, is being actively pursued. Learning histories are stored in public clouds such as Amazon Web Services and Google Cloud Platform, and are protected by the large-scale disaster recovery mechanism of cloud storage. However, the outbreak of war or regional conflict, or the occurrence of a disaster that threatens the survival of a country itself, makes it difficult to provide public cloud services, which are merely private commercial services. We must ensure that the learning history of learners, which cannot be recovered once it is lost, is stored and maintained even in multi-hazard situations.In this study, we construct a learning history storing framework that applies blockchain technology in order to store and maintain learners' learning history even in multi-hazard situations. By applying the decentralized and autonomous nature of blockchain technology, the learning history can be maintained and restored even in the event of a functional failure or data loss of information communication networks or data centers due to a disaster. In this presentation, we describe the design of a blockchain mechanism for learning history retention and describe a learning history retention mechanism linked to an existing Learning Management System. The design and effectiveness of the prototype system implemented for validation are also described.
COVID-19 diagnosis using AI
Advanced Data Processing Techniques
Environmental and Biological Research in Conflict Zones