Andrei Tchernykh - Academia.edu (original) (raw)

Papers by Andrei Tchernykh

Confidential data security is associated with the cryptographic primitives, asymmetric encryption... more Confidential data security is associated with the cryptographic primitives, asymmetric encryption, elliptic curve cryptography, homomorphic encryption, cryptographic pseudorandom sequence generators based on an elliptic curve, etc. For their efficient implementation is often used Residue Number System that allows executing additions and multiplications on parallel computing channels without bit carrying between channels. A critical operation in Residue Number System implementations of asymmetric cryptosystems is base extension. It refers to the computing a residue in the extended moduli without the application of the traditional Chinese Remainder Theorem algorithm. In this work, we propose a new way to perform base extensions using a Neural Network of a final ring. We show that it reduces 11.7% of the computational cost, compared with state-of-the-art approaches.

The International Workshop on Information, Computation, and Control Systems for Distributed Environments, 2020

When designing and using distributed storage systems with cloud technology, the security issues b... more When designing and using distributed storage systems with cloud technology, the security issues become crucial. One of the promising mechanisms is the computationally secure threshold secret sharing scheme. We propose a computationally secure secret sharing scheme based on the minimally redundant modular code. It reduces the computational complexity of data encoding and decoding and reduce data redundancy. We show that it is computationally secure and provides data redundancy equivalent to the redundancy of the Rabin system. We demonstrate that the minimally redundant modular code does not satisfy the criterion of compactness of a sequence, but it can be used as an asymptotically ideal secret sharing scheme.

Springer eBooks, May 28, 2008

This paper presents a genetic algorithm for a scheduling problem frequent in printed circuit boar... more This paper presents a genetic algorithm for a scheduling problem frequent in printed circuit board manufacturing: a hybrid flowshop with unrelated machines, sequence dependent setup time and machine availability constraints. The proposed genetic algorithm is a modified version of previously proposed genetic algorithms for the same problem. Experimental results show the advantages of using new crossover operator. Furthermore, statistical tests confirm the superiority of the proposed variant over the state-of-the-art heuristics.

Programming and Computer Software, Nov 28, 2022

Programming and Computer Software, 2021

Abstract The paper discusses optimization issues of training Artificial Neural Networks (ANNs) us... more Abstract The paper discusses optimization issues of training Artificial Neural Networks (ANNs) using a nonlinear trigonometric polynomial function. The proposed method presents the mathematical model of an ANN as an information transmission system where effective techniques to restore signals are widely used. To optimize ANN training, we use energy characteristics assuming ANNs as data transmission systems. We propose a nonlinear layer in the form of a trigonometric polynomial that approximates the “syncular” function based on the generalized approximation theorem and the wave model. To confirm the theoretical results, the efficiency of the proposed approach is compared with standard ANN implementations with sigmoid and Rectified Linear Unit (ReLU) activation functions. The experimental evaluation shows the same accuracy of standard ANNs with a time reduction of the training phase of supervised learning for the proposed model.

We analyze performance properties of list scheduling algorithms under various dynamic assumptions... more We analyze performance properties of list scheduling algorithms under various dynamic assumptions and different levels of knowledge available for scheduling, considering the case of unit execution time tasks. We focus on bounds for the ISF (immediate successors first) and MISF (maximum number of immediate successors first) scheduling strategies and show the difference from other bounds obtained for the same problem. Finally, we present case studies and experimental results to assess the average behavior.

IEEE Transactions on Services Computing

Desktop clouds (DC) provide services in non-stationary environments that face reliability and per... more Desktop clouds (DC) provide services in non-stationary environments that face reliability and performance threats not found in traditional clusters and datacenters. The idle resources available on computers can be claimed by users, turned off and faulted any time. For instance, platforms such as CernVM and UnaCloud harvest idle resources on computer labs to run virtual machines and support scientific applications. These platforms deal with interruptions and interferences caused by both users and applications. This non-stationarity is one of the main sources of issues in the design of reliable desktop cloud infrastructures that are capable of mitigating their own faults and errors. Based on a fault analysis that we have been carrying out and refining for a couple of years, we have found that reliability problems begin as the number of virtual machines that are going to be executed increases; these virtual machines must first be provisioned in the physical machines where they will be ...

Programming and Computer Software

Due to continuing advances in computing and communication technology innovation has become one of... more Due to continuing advances in computing and communication technology innovation has become one of the most important fields. It drives transformations in human life, engineering, business, entertainment, education, etc. The special issue addresses these challenging trends. It overviews the latest advances and opportunities in interdisciplinary areas of advanced computing, software engineering, multi-objective resource optimization, etc. It features nineteen papers selected from thirty-nine submitted by authors from eight countries. The paper "Formal Verification of Blockchain-Based Tender Systems" addresses that tenders are developed using centralized unverified systems, which reduce transparency, fairness, and trust in the process, and the ability to detect malicious attempts to manipulate the process. This paper proposes using a combination of Satisfiability Module Theories (SMT) and Blockchain to deal with this problem. The authors argued that SMT provides a formal analysis to prove the correctness of tender and offers properties ensuring system reliability, while Blockchain claims to provide decentralization and a chain of distributed and decentralized records linked so that integrity is ensured. This combination allows a formal, verified and decentralized system to make electronic procurement tenders more reliable, transparent, and fair. The paper "Automatic code generation of usercentered serious games: A decade in review" presents a review covering a decade of information from January 2012 to June 2022. It is divided into two parts: one study about serious games with model-driven engineering and another study about user-centered serious games. The main objective is to know the literature that helps to mitigate the costs and time of software development of serious games. The overall conclusion is that there is still work to be done to combine serious user-centered games and automatic generation. The paper "Building Adaptable Dashboards for Smart Cities: Design and Evaluation" focuses on the idea that dashboards aim to provide users with information to support decision-making. It is essential to adapt the visualization of the information provided to their needs and preferences. To address this necessity, the authors performed a literature review. Based on

Programming and Computer Software, Dec 1, 2021

Electronics, Oct 27, 2020

Number comparison has long been recognized as one of the most fundamental non-modular arithmetic ... more Number comparison has long been recognized as one of the most fundamental non-modular arithmetic operations to be executed in a non-positional Residue Number System (RNS). In this paper, a new technique for designing comparators of RNS numbers represented in an arbitrary moduli set is presented. It is based on a newly introduced modified diagonal function, whose strictly monotonic properties make it possible to replace the cumbersome operations of finding the remainder of the division by a large and awkward number with significantly simpler computations involving only a power of 2 modulus. Comparators of numbers represented in sample RNSs composed of varying numbers of moduli and offering different dynamic ranges, designed using various methods, were synthesized for the 65 nm technology. The experimental results suggest that the new circuits enjoy a delay reduction ranging from over 11% to over 75% compared to the fastest circuits designed using existing methods. Moreover, it is achieved using less hardware, the reduction of which reaches over 41%, and is accompanied by significantly reduced power-consumption, which in several cases exceeds 100%. Therefore, it seems that the presented method leads to the design of the most efficient current hardware comparators of numbers represented using a general RNS moduli set.

Communications in computer and information science, 2019

This article describes the application of parallel computing techniques for efficiently processin... more This article describes the application of parallel computing techniques for efficiently processing large volumes of data from ITS. This is a relevant problem in nowadays societies, especially when working under the novel paradigm of smart cities. The proposed approach applies parallel multithreading computing for processing Global Positioning System records for a case study on the Intelligent Transportation System in Montevideo, Uruguay. The experimental analysis is performed on a high performance computing platform, considering a large volume of data and different computing resources. The main results indicate that the proposed approach allows achieving good speedup values, thus reducing the execution time to process more than 120 GB of data from 921 to 77 min, when using 32 threads. In addition, a web application to illustrate the results of the proposed approach for computing the average speed of public transportation in Montevideo, Uruguay, is described.

Mathematics, Dec 27, 2021

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

This article presents a multiobjective evolutionary approach for computing flight plans for a fle... more This article presents a multiobjective evolutionary approach for computing flight plans for a fleet of unmanned aerial vehicles to perform exploration and surveillance missions. The static off-line planning subproblem is addressed, which is useful to determine initial flight routes to maximize the explored area and the surveillance of points of interest in the zone. A specific flight planning solution is developed, to be applied in low-cost commercial Bebop 2. The experimental analysis is performed in realistic instances of the surveillance problem. Results indicate that the proposed multiobjective evolutionary algorithm is able to compute accurate flight plans, significantly outperforming a previous evolutionary method applying the linear aggregation approach.

The use of cloud technologies for processing confidential data requires a solution to the data se... more The use of cloud technologies for processing confidential data requires a solution to the data security problem. One of the mechanisms to solve it is homomorphic encryption. However, homomorphic encryption only allows the arithmetic operations of addition and multiplication to be performed over encrypted numbers. Consequently, when implementing algorithms for matrix algebra, artificial neural networks, and deep learning, it becomes necessary to implement the comparison operation in a homomorphic cipher. In this paper, we study methods for comparison operations in a homomorphic cipher. One of the methods is to use the subtraction of numbers and determine the sign of a number. Two families of polynomials and their composition are used to approximate the sign function. We provide estimates of the accuracy of the sign function approximation obtained as a result of modeling and show that they are 1.98 times better than the state-of-the-art theoretical estimate for polynomials fn(x)f_{n}(x)fn(x). Also, we show that the theoretical estimate of gn(x)g_{n}(x)gn(x) is not applicable for nleq4n\leq 4nleq4.

The numerical simulation of complex astrophysical problems requires high-performance computing du... more The numerical simulation of complex astrophysical problems requires high-performance computing due to the large size of the problems and variety of simulated physical processes. In this paper, we present a new framework for the numerical simulation of astrophysical fluid dynamics. It is based on the mechanisms of combining distributed and parallel computing techniques, advanced vectorization for KNL, and Skylake-SP CPU architectures. Our new HydroBox3D framework uses large 3D meshes to solve problems such as the dynamics of stars or galaxies. In our framework, we use computational nodes with a large amount of memory (RAM or Intel Optane in memory mode) for mesh processing and typical computational nodes for the numerical simulation of astrophysical problems. We use MPI both for send/receive operations between computational nodes and for sending processed data for calculations from data nodes. For optimization of calculations, memory, and CPU usage, we use data vectorization, FMA3, and AVX-512 instructions for Intel Xeon Phi 72XX and Intel Xeon Scalable processors. Benchmark results on different CPU and MIC devices show the effectiveness of the proposed solution.

Lecture Notes in Computer Science, 2019

Computation (Basel), Jan 13, 2022