Devising a method to identify an incoming object based on the combination of unified information spaces
DOI:
https://doi.org/10.15587/1729-4061.2021.229568Keywords:
unified information space, object identification, parameter of the incoming object, information object, search methodAbstract
This paper suggests a method to search for an incoming object in order to identify its unambiguously, based on the integration of information spaces into intermediate unified information space. At the same time, the incoming object identification process involves appropriate attributes.
This paper describes the process of information object arrangement within a unified information space that forms for a set of dynamically changing objects. It should be noted that each subject in the set collects information about the environment, including interaction with other objects. In the process of forming a unified information space, the information system collects information from data sources that are represented in different formats. The system then converts this information and forms a unified information space, thereby providing users with information about objects.
A two-tier system of connections at the global (cloud) and local (fog) levels of interactions has been considered. At the same time, it should be noted that a unified information space formation requires the implementation of tools to support the transformation of information objects; that necessitates the implementation of translators ‒ special converters at different levels.
A method to combine information spaces into an intermediate unified information space has been proposed; analysis was performed to determine the time and efficiency of the search for incoming objects within it.
It was experimentally established that the more parameters that describe an information object, the less the time to identify an object depends on the length of the interval.
It has also been experimentally shown that the efficiency of finding incoming objects tends to be a directly proportional dependence while reducing the length of the interval and increasing the number of parameters, and vice versa
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Copyright (c) 2021 Вадим Евгеньевич Мухин, Валерий Викторович Завгородний, Ярослав Игоревич Корнага, Анна Анатольевна Завгородняя, Евгений Владимирович Крылов, Андрей Владимирович Рыбалочка, Василий Игоревич Корнага, Роман Владимирович Белоус
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