Персона: Русаков, Виктор Анатольевич
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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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Виктор Анатольевич
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- ПубликацияТолько метаданныеOn Markov Chains and Some Matrices and Metrics for Undirected Graphs(2020) Rusakov, V. A.; Русаков, Виктор Анатольевич© Springer Nature Switzerland AG 2020.Metric tasks often arise as a simplification of complex and practically important problems on graphs. The correspondence between the search algorithms of the usual shortest paths and Markov chains is shown. From this starting point a sequence of matrix descriptions of undirected graphs is established. The sequence ends with the description of the explicit form of the Moore-Penrose pseudo inversed incidence matrix. Such a matrix is a powerful analytical and computational tool for working with edge flows with conditionally minimal Euclidian norms. The metrics of a graph are represented as its characteristics generated by the norms of linear spaces of edge and vertex flows. The Euclidian metric demonstrates the advantages of the practice of solving problems on graphs in comparison with traditional metrics based on the shortest paths or minimal cuts.
- ПубликацияТолько метаданныеUsing Metrics in the Analysis and Synthesis of Reliable Graphs(2020) Rusakov, V. A.; Русаков, Виктор Анатольевич© 2020, Springer Nature Switzerland AG.The interaction of intelligent agents implies the existence of an environment to support it. The usual representations of this environment are graphs with certain properties. Reliability is one of the most important characteristics of such graphs. Traditional metrics, i.e. the usual shortest paths and minimal cuts, form the basis of the traditional measures of reliability. The analyzing and synthesizing of reliable graphs using the Euclidian metric are described. The Euclidian metric allows us to achieve better results in doing this compared to the cases of using traditional metrics. The described approach can be used in the analysis and synthesis of the environment supporting the intercommunication of intelligent agents in conditions of limited resources to organize the structure of this interaction.
- ПубликацияТолько метаданныеUsing Metrics in the Throughput Analysis and Synthesis of Undirected Graphs(2021) Rusakov, V. A.; Русаков, Виктор Анатольевич© 2021, Springer Nature Switzerland AG.The usual representations of the communication environment are graphs with certain properties. Like reliability, throughput is one of the most important characteristics of such graphs. Metric tasks often arise when simplifying complex and practically important problems on graphs. A traditional metric, such as the usual shortest paths, forms the basis of the traditional throughput index. In this case, the metric is used to obtain the distribution of multi-colour flows in graphs more complex than trees. To achieve better results than when using ordinary shortest paths, one can use the Euclidian metric. If one starts with the Kleinrock formula for the average packet delay, then the Euclidian (quadratic) metric allows one to practically refuse multiple distributions over the shortest paths with variable edge lengths in the cut saturation procedures. The same Euclidian metric describes the distribution of the flow of any colour in an arbitrary graph as the best approximation to the ideal distribution in a complete graph in the sense of quadratic deviation. Such independence of the result from the Kleinrock formula demonstrates the effectiveness of linear metric models in the throughput analysis and synthesis of graphs. The Euclidian metric also allows you to introduce the throughput index of an arbitrary graph into these tasks in the form of an abstract measure. Therefore in such tasks one can completely disregard the distribution of the flows. Theoretical results are illustrated by an example of graph synthesis.
- ПубликацияТолько метаданныеOn the Regularity of the Bias of Throughput Estimates on Traffic Averaging(2021) Rusakov, V. A.; Русаков, Виктор Анатольевич© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.The interaction of intelligent agents implies the existence of an environment to support it. The usual representations of this environment are graphs with certain properties. Like reliability, throughput is one of the most important characteristics of such graphs. When evaluating throughput in the analysis and synthesis of graphs, a reasonable combination of heuristic and strict approaches is used. In practice, this leads to the use of graph metrics. Usual shortest paths are widely used as part of the various multi-colour flow distribution procedures. The analytical capabilities of the Euclidian metric can achieve much more than just obtaining such a distribution. Such a metric allows us to introduce an abstract measure of the (quadratic) proximity of an arbitrary graph to a complete graph. This measure can be used as a single indicator of the reliability and throughput of the graph. Other conditions for tasks on graphs can be attributed to restrictions. A traffic matrix is one of these conditions. Non-stationarity of traffic when averaging over time can significantly reduce the accuracy of the estimates of throughput. The described dependencies of the throughput on the traffic’s non-stationarity can be used in the analysis and synthesis of the communication environment when organizing the structure of the interaction of intelligent agents in the conditions of limited resources. These dependencies are verified by the results of numerical experiments.
- ПубликацияТолько метаданныеUsing the Euclidean Metric When Studying Multicolor Flows in Undirected Graphs(2024) Rusakov, V. A.; Русаков, Виктор Анатольевич