Abstract

In industry, more and more money is being invested in transition to new standards - Industry 4.0. The network of weather stations (Network) required by Industry 4.0 must capture and transmit data exceeding 200 times the amount of current data and have transmission delays not exceeding 30 seconds. The main requirement of Industry 4.0 for the Network is the high efficiency of delivering reliable data to a consumer. If a Network element fails, the consumer loses data not only of the failed element, but also of all elements transmitting their data through it. That is, the consumer does not receive reliable data, the probability of completing a task by the entire Network becoming less. The Network structure maximizing the probability of executing the tasks by the Network has been chosen in the article. The laws of distribution describing appearance or disappearance of Network elements are unknown and impossible to be obtained, therefore, the survivability index of the Network should not depend on the laws of distribution, that is, it should be incredible. It is the d-invariantism, the indicator showing the uniform distribution of weights (significance) among the structural elements. If the significance of all the arcs/ nodes is the same, the d-invariance equals 1, that is, the structure does not care which element will be deleted. If several structures with the same d-invariantism are possible on the given sets, then, to compare the structures with each other, we propose to use the indicator of structure quality, revealing the structure with the least average number of bonds per node. Using the indicators described above, the following structures have been evaluated: star, fully connected structure, tire, hypercube, lattice, torus, mesh, circulant. Having analyzed these structures, the following conclusions can be drawn: ring-containing structures are more survivable; the most survivable structure in the sense of d-invariantism is the circulant D (16; 1,7). These indicators allow to obtain the maximum possible probability of executing the tasks by the Network.

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