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Математическая модель оптимального размещения распределённой базы данных по узлам ЛВС на базе двухуровневой клиент-серверной архитектуры

Математическая модель оптимального размещения распределённой базы данных по узлам ЛВС на базе двухуровневой клиент-серверной архитектуры

Abstract

Using a device for close exponential networks of mass service a mathematical model for solving the problem of getting integral indexes of distributed information system on the basis of local computing network using two-level architecture “client-server” was worked out. The peculiarity of the model being worked out is in making a selective choice of information at the server and via the channel of communication not the full data base is transmitted but some separate parts of it, which satisfy the conditions of SQL-request search. Using the developed earlier heuristic algorithm the problem of optimal placing the distributed data base onto the local computing system knots according to the criterion of minimal average time of system reaction for users’ requests was solved. The results of numerical experiments are given.

В данной статье с использованием аппарата замкнутых экспоненциальных сетей массового обслуживания (СеМО) разработана математическая модель решения задачи об оптимальном размещении распределённой базы данных (РБД) по узлам локальной вычислительной сети (ЛВС) на базе двухуровневой клиент-серверной архитектуры по критерию минимума среднего времени реакции системы на запросы пользователей. Приведены результаты численных экспериментов.

Keywords

РАСПРЕДЕЛЁННАЯ БАЗА ДАННЫХ, СЕЛЕКТИВНАЯ ВЫБОРКА ИНФОРМАЦИИ, SQL-ЗАПРОС, РАСПРЕДЕЛЁННАЯ ИНФОРМАЦИОННАЯ СИСТЕМА, ТРАНЗАКЦИЯ, ПРОСТРАНСТВО СОСТОЯНИЙ СИСТЕМЫ, СТАЦИОНАРНАЯ ВЕРОЯТНОСТЬ, ПЕРЕХОДНАЯ ВЕРОЯТНОСТЬ, ИНТЕНСИВНОСТЬ ОБСЛУЖИВАНИЯ, МАТРИЦА ОБЪЁМОВ ИНФОРМАЦИИ, ВРЕМЯ РЕАКЦИИ СИСТЕМЫ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold