Кафедра "Комп'ютерна інженерія та програмування"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/1095

Офіційний сайт кафедри https://web.kpi.kharkov.ua/cep

Від 26 листопада 2021 року кафедра має назву – "Комп’ютерна інженерія та програмування"; попередні назви – “Обчислювальна техніка та програмування”, “Електронні обчислювальні машини”, первісна назва – кафедра “Математичні та лічильно-вирішальні прилади та пристрої”.

Кафедра “Математичні та лічильно-вирішальні прилади та пристрої” заснована 1 вересня 1961 року. Організатором та її першим завідувачем був професор Віктор Георгійович Васильєв.

Кафедра входить до складу Навчально-наукового інституту комп'ютерних наук та інформаційних технологій Національного технічного університету "Харківський політехнічний інститут". Перший випуск – 24 інженери, підготовлених кафедрою, відбувся в 1964 році. З тих пір кафедрою підготовлено понад 4 тисячі фахівців, зокрема близько 500 для 50 країн світу.

У складі науково-педагогічного колективу кафедри працюють: 11 докторів технічних наук, 21 кандидат технічних наук, 1 – економічних, 1 – фізико-математичних, 1 – педагогічних, 1 доктор філософії; 9 співробітників мають звання професора, 14 – доцента, 2 – старшого наукового співробітника.

Переглянути

Результати пошуку

Зараз показуємо 1 - 6 з 6

Evaluation model of the recovery processes of non-markovian systems, considering the elements unreliability under arbitrary distribution laws
(Національний технічний університет "Харківський політехнічний інститут", 2022) Raskin, Lev; Ivanchikhin, Yuriy; Sukhomlyn, Larysa; Svyatkin, Iaroslav; Korsun, Roman
The subject of the study is the reliability of recoverable non–Markovian systems, functioning of which is described by arbitrary distribution laws. The purpose of the article is to develop a mathematical model of the functioning of modern computer systems under arbitrary laws of the distribution of stay duration in each of the states, taking into account the recovery system and the provision of spare elements. The main task is to develop an adequate model of the system functioning process, taking into account the non-Markovian character of the processes occurring in the system, its possible large dimension, and the presence of a hierarchical recovery system. Based on this model, a method for calculating the density of the system recovery time distribution has been developed. At the same time, a universal four-parameter distribution is proposed to describe random processes occurring in the system. Using this approximation, the calculation of the desired parameter of the recovery flow is performed by solving the Volterra integral equation with a difference kernel.
Analysis of marсovian systems with a given set of selected states
(Національний технічний університет "Харківський політехнічний інститут", 2022) Raskin, Lev; Sukhomlyn, Larysa; Korsun, Roman
Analysis of stationary Marcovian systems is traditionally performed using systems of linear Kolmogorov differential equations. Such systems make it possible to determine the probability of the analyzed system being in each of its possible states at an arbitrary time. This standard task becomes more complicated if the set of possible states of systems is heterogeneous and some special subset can be distinguished from it, in accordance with the specifics of the system functioning. Subject of the study is technology development for such systems analysis. In accordance with this, the purpose of the work is to find the distribution law of the random duration of such a system's stay on a set of possible states until it falls into a selected subset of these states. Method for solving the problem is proposed based on splitting the entire set of possible states of the system into two subsets. The first of them contains a selected subset of states, and the second contains all the other states of the system. Now a subset of states is allocated from the second subset, from which a direct transition to the states of the first subset is possible. Next, a system of differential equations describing the transitions between the formed subsets is formed. The solution of this system of equations gives the desired result – distribution of the random duration of the system's stay until the moment of the first hit in the selected subset of states. The method allows solving a large number of practical problems, for example, in the theory of complex systems reliability with many different failure states. In particular, finding the law of the uptime duration distribution, calculating the average duration of uptime.
Semi-Markov reliability models
(Національний технічний університет "Харківський політехнічний інститут", 2022) Raskin, Lev; Sviatkin, Iaroslav; Ivanchikhin, Yuriy; Korsun, Roman
Traditional technologies for reliability analysis of semi-Markov systems are limited to obtaining a stationary state probability distribution. However, when solving practical control problems in such systems, the study of transient processes is of considerable interest. This implies the subject of research - the analysis of the laws of distribution of the system states probabilities. The goal of the work is to obtain the desired distribution at any time. The complexity of the problem solving is determined by the need to obtain a result for arbitrary distribution laws of the duration of the system's stay in each state before leaving. An easy-to-implement method for the analysis of semi-Markov reliability models has been suggested. The method is based on the possibility of approximating probability-theoretic descriptions of failure and recovery flows in the system using the Erlang distribution laws of the proper order. The developed computational scheme uses the most important property of Erlang flows, which are formed as a result of sieving the simplest Poisson flow. In this case, the semi-Markov model is reduced to the Markov one, which radically simplifies the analysis of real systems.
Analysis of multi-threaded markov systems
(Національний технічний університет "Харківський політехнічний інститут", 2021) Raskin, Lev; Sukhomlyn, Larysa; Sagaidachny, Dmytro; Korsun, Roman
Known technologies for analyzing Markov systems use a well-operating mathematical apparatus based on the computational implementation of the fundamental Markov property. Herewith the resulting systems of linear algebraic equations are easily solved numerically. Moreover, when solving lots of practical problems, this numerical solution is insufficient. For instance, both in problems of structural and parametric synthesis of systems, as well as in control problems. These problems require to obtain analytical relations describing the dependences of probability values of states of the analyzed system with the numerical values of its parameters. The complexity of the analytical solution of the related systems of linear algebraic equations increases rapidly along with the increase in the system dimensionality. This very phenomenon manifests itself especially demonstratively when analyzing multi-threaded queuing systems. Accordingly, the objective of this paper is to develop an effective computational method for obtaining analytical relations that allow to analyze high-dimensional Markov systems. To analyze such systems this paper provides for a decomposition method based on the idea of phase enlargement of system states. The proposed and substantiated method allows to obtain analytical relations for calculating the distribution of Markov system states. The method can be effectively applied to solve problems of analysis and management in high-dimensional Markov systems. An example has been considered.
Structural optimization in a multi-channel distributed mass service system
(Національний технічний університет "Харківський політехнічний інститут", 2021) Raskin, Lev; Sira, Oksana; Parfeniuk, Yurii; Sukhomlyn, Larysa
Problem of structural optimization in a distributed service system is solved by the example of system "Production - delivery - consumption" for mass market product. In this regard, the purpose of work is to develop a method for structural optimization of "Production - delivery - mass consumption" system, by introducing and rational placement of intermediate production points based on solving clustering problems with taking into account the peculiarities of calculating distances between city objects. To achieve the goal of the work, it is necessary to solve the following tasks: clustering of city objects, using the metric of city blocks, for a given number of groups for selected location of production and grouping centers; finding the best location for a given number of clustering centers; determination of a rational number of clustering centers. Task was solved in three stages. First stage - clustering a set of consumption objects for given intermediate delivery centers locations. The second stage - finding the best locations for a given number of intermediate delivery centers. The third stage - determination of the rational number of intermediate centers. Formulated problem is solved according to two criteria: combined length of delivery routes product consumers and the probability that a random delivery time exceeds the critical value. The numerical value of the second criterion is calculated on the assumption that for each path may be estimated value of the mean and variance delivery time. The appropriate number of production centers is determined by a simple comparison of system efficiency for several realistically possible options. An example of clustering problem solving in the metric of "city blocks" on a directed graph by both criteria is given.
Selection of the optimum route in an extended transportation network under uncertainty
(Національний технічний університет "Харківський політехнічний інститут", 2021) Raskin, Lev; Sira, Oksana; Parfeniuk, Yurii
Relevance. For a given values set of extensive transport network sections lengths an exact method has been developed for finding optimal routes. The method provides an approximate solution when the initial data - are random variables with known distribution laws, as well as if these data are not clearly specified. Fora special case with a normal distribution of the numerical characteristics of the network, solution is brought to the final results. Method. An exact method of deterministic routing is proposed, which gives an approximate solution in case of random initial data. The method is extended to the case when the initial data are described in theory of fuzzy sets terms. The problem of stability assessing of solutions to problems of control the theory under conditions of uncertainty of initial data is considered. Results. A method of optimal routes finding is proposed when the initial data are deterministic or random variables with known distribution densities. A particular case of a probabilistic -theoretical description of the initial data is considered when can be obtained a simple solution of problem. Proposed method for obtaining an approximate solution in the general case for arbitrary distribution densities of random initial data. The situation is common when the initial data are not clearly defined. A simple computational procedure proposed for obtaining a solution. A method for stability assessing of solutions to control problems adopted under conditions of uncertainty in the initial data, is considered.