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AUTOMATION OF SCIENTIFIC AND EDUCATIONAL RESEARCH OF MESSAGE NETWORKS SURVIVABILITY
German A. Ptitsyn, MTUCI, Moscow, Russia, isua.kaf@yandex.ru
Abstract
The construction of graphical and numerical dependencies in the calculation of survivability indicators (connectivity probabilities, structural, functional and streaming vitality) for typical structures of any size, and even more so for networks of arbitrary structure, require the use of computers, since the amount of calculations grows as 2n + 2r, where n — the number of nodes, r is the number of arcs under the condition of the binary state of network elements, which follows from the assumption that after the attack the network continues to transmit (transport) messages if at least one coherent fragment remains in it m two knots or more. In this case, the survivability of the network becomes greater than zero. Evaluation of structural and functional survivability is associated with the use of a complete exhaustive search of random network states after an attack on arcs and nodes from normal operating conditions (the number of damaged elements is zero) and until the network is completely destroyed (all network elements have died). The program used a graphical input network topology. The program interface contains five windows: initial data: topology, management, a table with numerical results (summary), graphs of survivability versus probability or of the number (share) of affected elements and a window of analytical expressions. The dependence of the survivability indicators of networks on the size with a constant fiz-number of redundant arcs, and, conversely, the dependence of survivability on f-res at a constant network size, is established. An instruction was given to the user of the program. Ñertificates of state registration were received for the survivability study programs.
Keywords: networks of messages, attack on arcs, indicators of survivability, method of complete damage search, increase in the volume of calculations, software implementation of calculations.
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Information about authors:
German A. Ptitsyn, Ph.D., Associate Professor, Department of Intelligent Systems in Management and Automation, MTUCI, Moscow, Russia