
Gleb RadchenkoSAL Silicon Austria Labs · Collaborative Perception and Learning
Gleb Radchenko
Doctor of Philosophy
About
91
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Introduction
Gleb Radchenko currently works at the Silicon Austria Labs (SAL). Gleb does research in Distributed Computing, Software Engineering and Parallel Computing, Distributed and Collaborative Machine Learning.
Additional affiliations
October 2013 - June 2016
Publications
Publications (91)
Microservice architecture is a cloud application design pattern that implies that the application is divided into a number of small independent services, each of which is responsible for implementing of a certain feature. The need for continuous integration of developed and/or modified microservices in the existing system requires a comprehensive v...
The concept of grid computing has become a standard way of collaboration of scientific community computational resources while solving extra-large and resource-intensive tasks. On the other hand, the "cloud computing" concept is gaining increasing popularity in the field of provision of computing resources to an end-user on demand. PaaS (Platform a...
Cloud computing became very popular during the last few decades. It provides convenient access to remote computing resources for individual users and organizations. However, there are still security issues arise if the private data is transmitted to the public cloud for processing. This issue can be resolved with private cloud systems. In this pape...
A private PaaS enables enterprise developers to leverage all the benefits of a public PaaS to deploy, manage, and monitor applications, while meeting the security and privacy requirements your enterprise demands. In this paper we propose the design and implementation of a Mjolnirr private cloud platform for development of the private PaaS cloud inf...
Computer-Aided Engineering (CAE) systems demand a vast amount of computing resources to simulate modern hi-tech products. In this paper we consider the problem-oriented approach to access remote distributed supercomputer resources using the concept of distributed virtual test bed (DiVTB). DiVTB provides a problem-oriented user interface to distribu...
Contemporary computing systems are commonly characterized in terms of data-intensive workflows, that are managed by utilizing large number of heterogeneous computing and storage elements interconnected through complex communication topologies. As the scale of the system grows and workloads become more heterogeneous in both inner structure and the a...
Contemporary control processes and methods in multi-scale, cyber-physical systems require precise data collection at various levels, timely transmission, and analysis involving large number of computing and storage elements connected within high-performance permissioned consensus networks. For example, in transport networks, resources tend to form...
As the Internet of Things (IoT) becomes a part of our daily life, there is a rapid growth in connected devices. A well-established approach based on cloud computing technologies cannot provide the necessary quality of service in such an environment, particularly in terms of reducing data latency. Today, fog computing technology is seen as a novel a...
As the population grows, the need for a quality level of medical services grows correspondingly, so does the demand for information technology in medicine. The concept of "Smart Healthcare" offers many approaches aimed at solving the acute problems faced by modern healthcare. In this paper, we review the main problems of modern healthcare, analyze...
This article proposes an approach to the problem of computational capacities analysis of the computing continuum via theoretical framework of equilibrium phase-transitions and numerical simulations. We introduce the concept of phase transitions in computing continuum and show how this phenomena can be explored in the context of workflow makespan, w...
The protection of data processing is emerging as an essential aspect of data analytics, machine learning, delegation of computation, Internet of Things, medical and financial analysis, smart cities, genomics, non-disclosure searching, among others. Often, they use sensitive information that cannot be protected by traditional cryptosystems. Homomorp...
Classical machine learning modeling demands considerable computing power for internal calculations and training with big data in a reasonable amount of time. In recent years, clouds provide services to facilitate this process, but it introduces new security threats of data breaches. Modern encryption techniques ensure security and are considered as...
The fog computing paradigm has become prominent in stream processing for IoT systems where cloud computing struggles from high latency challenges. It enables the deployment of computational resources between the edge and cloud layers and helps to resolve constraints, primarily due to the need to react in real time to state changes, improve the loca...
The secure and efficient processing of private information in the cloud computing paradigm is still an open issue. New security threats arise with the increasing volume of data into cloud storage, where cloud providers require high levels of trust, and data breaches are significant problems. Encrypting the data with conventional schemes is consider...
Digital twins of processes and devices use information from sensors to synchronize their state with the entities of the physical world. The concept of stream computing enables effective processing of events generated by such sensors. However, the need to track the state of an instance of the object leads to the impossibility of organizing instances...
Clouds can significantly reduce the cost and time of business solutions. However, cloud services introduce significant security and privacy challenges when they process sensitive information. For instance, a dataset for machine learning could contain delicate information that traditional encryption approaches cannot protect during data analysis. Ho...
Digital twins of processes and devices use information from sensors to synchronize their state withthe entities of the physical world. The concept of stream computing enables effective processing of events gen-erated by such sensors. However, the need to track the state of an instance of the object leads to the impossi-bility of organizing instance...
The security of data storage, transmission, and processing is emerging as an important consideration in many data analytics techniques and technologies. For instance, in machine learning, the datasets could contain sensitive information that cannot be protected by traditional encryption approaches. Homomorphic encryption schemes and secure multi-pa...
The secure and efficient processing of private information in the cloud computing paradigm is still an open issue. New security threats arise with the increasing volume of data into cloud storage, where cloud providers require high levels of trust, and data breaches are significant problems. Encrypting the data with conventional schemes is consider...
IoT environment has a dynamic nature with high risks of confidentiality, integrity, and availability violations. The loss of information, denial of access, information leakage, collusion, technical failures, and data security breaches are difficult to predict and anticipate in advance. These types of non-stationarity are one of the main issues in t...
Cloud storage is one of the most popular models of cloud computing. It benefits from a shared set of configurable resources without limitations of local data storage infrastructures. However, it brings several cybersecurity issues. In this work, we address the methods of mitigating risks of confidentiality, integrity, availability, information leak...
Properties of redundant residue number system (RRNS) are used for detecting and correcting errors during the data storing, processing and transmission. However, detection and correction of a single error require significant decoding time due to the iterative calculations needed to locate the error. In this paper, we provide a performance evaluation...
Digital Twin is a virtual representation of a technological process or a piece of equipment, that supports monitoring, control and state prediction based on the data, gathered from the sensor networks. To parallelize event processing and produce near-real-time insights over data streams, Digital Twin should be implemented based on an Event-Driven a...
Mobile Ad-Hoc Networks (MANET) require special approaches to the design and selection of data transmission and security algorithms Nodes mobility and dynamic topology give rise to two key problems of MANET – the difficulty of ensuring confidentiality when transmitting data through a network and the complexity of organizing reliable data transfer. T...
Cloud computing systems have become widely used for Big Data processing, providing access to a wide variety of computing resources and a greater distribution between multi-clouds. This trend has been strengthened by the rapid development of the Internet of Things (IoT) concept. Virtualization via virtual machines and containers is a traditional way...
Cloud computing systems have become widely used for Big Data processing, providing access to a wide variety of computing resources and a greater distribution between multi-clouds. This trend has been strengthened by the rapid development of the Internet of Things (IoT) concept. Virtualization via virtual machines and containers is a traditional way...
Mobile Ad-Hoc Networks (MANET) require special approaches to the design and selection of data transmission and security algorithms Nodes mobility and dynamic topology give rise to two key problems of MANET - the difficulty of ensuring confidentiality when transmitting data through a network and the complexity of organizing reliable data transfer. T...
В последнее время наблюдается взрывной рост в развитии концепции цифровой индустрии. Одним из важнейших элементов этой концепции является применение методов математического моделирования и ин-теллектуального анализа данных для создания моделей производственных процессов и конечной продукции, базирующихся на обработке сигналов, поступающих с интелле...
Knowing the mobility patterns of citizens using public transportation is an important issue for modern smart cities. Mobility information is crucial for designing and planning an urban transportation system able to provide good service to citizens. We address two relevant problems related to public transportation systems: the analysis of mobility p...
Lightweight virtualization technology has emerged as an alternative to traditional hypervisor-based virtualization. Containers based on an operating system level virtualization have shown superior performance and more flexibility than virtual machines. Both factors encourage their fast adoption and wide use in cloud environments. Container technolo...
The conservation efforts of the endangered Saimaa ringed seal depend on the ability to reliably estimate the population size and to track individuals. Wildlife photo-identification has been successfully utilized in monitoring for various species. Traditionally, the collected images have been analyzed by biologists. However, due to the rapid increas...
The Digital Twin is a hierarchical system of mathematical models and computational methods, which provides near real-time synchronization between the state of the real-world process and its virtual copy. It can be represented as a computational workflow, where the nodes are the computing services and other digital twins linked together by the data...
Cloud security issues are important factors for data storage and processing. Apart from the existing security and reliability problems of traditional distributed computing, there are new security and reliability problems. They include attacks on a virtual machine, attacks on the synchronization keys, and so on. According to the assessment of intern...
In this paper, we formulate configurable cloud-based VoIP call allocation problem as a special case of dynamic multi-objective bin-packing. We consider voice quality influenced by CPU stress, cost
contributed by the number of billing hours for Virtual Machines (VMs) provisioning, and calls placed on hold due to under-provisioning resources. We dist...
In this paper, we present a Big Data analysis paradigm related to smart cities using cloud computing infrastructures. The proposed architecture follows the MapReduce parallel model implemented using the Hadoop framework. We analyse two case studies: a quality-of-service assessment of public transportation system using historical bus location data,...
In this paper, we propose a timetable optimization method based on a Multiobjective Cellular genetic algorithm to tackle the multiple vehicle-type problems. The objective is to determine bus assignment in each time period to optimize a quality of service and transport operating cost. The quality of service, represented by the unsatisfied user deman...
We consider cryptosystems for homomorphic encryption schemes based on the Residue Number System (RNS) and Secret Sharing Schemes. One of their disadvantages is that they are directly related to data redundancy, and hence, increasing the size of the storage. To minimize it, homophonic encryption can be combined with the arithmetic coding known as Ch...
In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechani...
The concept of "Industry 4.0" considers smart factories as data-driven and knowledge enabled enterprise intelligence. In such kind of factory, manufacturing processes and final products are accompanied by virtual models -- Digital Twins. To support Digital Twins concept, a simulation model for each process or system should be implemented as indepen...
The automation capabilities and flexibility of computing resource scaling in cloud environments require novel approaches to application design. The microservice architectural style, which has been actively developing in recent years, is an approach to design a single application as a suite of small services. Continuous integration approach demands...
This paper addresses error correction codes approach in order to improve the performance of BOINC under uncertainty of users' behavior. Redundant Residue Number System (RRNS) moduli set of the special form provides correction of user unfairness, reliability, decreased redundancy and load of the computing network. Error correction code in RRNS is im...
Cloud computing has become a part of people's lives. However, there are many unresolved problems with security of this technology. According to the assessment of international experts in the field of security, there are risks in the appearance of cloud collusion in uncertain conditions. To mitigate this type of uncertainty, and minimize data redund...
The article examines the education system in the direction of "Software Engineering" in Russia for bachelor's, master's and postgraduate studies. The results of the analysis of Federal state educational standards in the direction of "Software Engineering", based on the comparison of competencies to the international body of knowledge on software en...
Web-based systems test techniques developed rapidly over the past years. Continuous integration approach demanded rejection of manual testing methods, and transition to fully automated methods, covering all application from the source code of core services to the user interface and API correctness. Every year there are dozens of new approaches to c...
Web-based systems test techniques developed rapidly over the past years. Continuous integration approach demanded rejection of manual testing methods, and transition to fully automated methods, covering all application from the source code of core services to the user interface and API correctness. Every year there are dozens of new approaches to c...
Energy consumption represents a large percentage of the operational expenses in data centers. Most of the existing solutions for energy-aware scheduling are focusing on job distribution and consolidation between computing servers, while network characteristics are not considered. In this paper, we propose a model of power and network-aware scheduli...
Problem-solving environments " recently became a widely accepted approach to providing computational resources to solve complex eScience problems. This approach represents a problem as a work-flow, orchestrating a set of various computational services. The existing cloud computing resources planning methods do not take into account a relation betwe...
Today we see a significantly increased use of problem-oriented approach to the development of cloud computing environment scheduling algorithms. There are already several such algorithms. However, a lot of these require that the tasks within a single job are independent and do not account for the execution of each task and the volume of data transm...
In this paper, we describe a solution for monitoring of parking availability based on computer vision. It allows us to detect and track cars in a parking lot, while collected historical data helps us to predict availability status of parking during the day based on data mining techniques. Parking Monitoring System tracks availability based on an an...
Modern computational experiments imply that the resources of the cloud computing environment are often used to solve a large number of tasks, which differ only in the values of a relatively small set of simulation parameters. Such sets of tasks may occur while implementing multivariate calculations aimed at finding the simulation parameter values,...
In this paper, we present a Big Data analysis paradigm related to smart cities using cloud computing infrastructures. The proposed architecture follows the MapReduce parallel model implemented using the Hadoop framework. We analyse two case studies: a quality-of-service assessment of public transportation system using historical bus location data,...
Abstract. For efficient use of high-performance computing resources while implementing Computational Science methods for the study of physical, biological and social problems one can use problem-oriented distributed computing environments approach. They provide users with transparent access to the solution of specific classes of applications based...
Due to the wide spread of cloud computing, arises actual question about architecture, design and implementation of cloud applications. The microservice model describes the design and development of loosely coupled cloud applications when computing resources are provided on the basis of automated IaaS and PaaS cloud platforms. Such applications cons...
The use of a component-oriented approach to the development of distributed applications can significantly extend the scalability of the software systems. In this article we describe the Mjolnirr platform, providing deployment of private cloud PaaS systems, based on the component-oriented approach. Any library or Java application can be implemented...