IT solutions architecture model: creation, generation of solutions
DOI:
https://doi.org/10.47813/2782-2818-2024-4-2-0212-0220Keywords:
architecture of IT solutions, generation of solutions, model of IT solutions, bifurcation, measure of information, entropy.Abstract
Possible decisions on the construction of the architecture of IT solutions are considered based on the application of the principles of causality, bifurcations and cognition, as well as technologies for constructing scenarios and developing management decisions that are directly related to the laws of computer science. Possible solutions for developing a model are proposed that include: monitoring processes related to enterprise architecture and the architecture of IT solutions; performing analysis of monitoring results; identification of preferences of governing bodies (priority ranking); substantiation of the presence of information uncertainty in possible options for developed solutions. The generation of proposed solutions involves identifying trends and changes in the external environment and within the enterprise, technologies for developing possible strategies for transition from one state to another. When building a model for developing IT solutions, it is proposed to: evaluate the properties, simplicity and capabilities of the architecture based on the use of the ArchiMate modeling tool; measure the impact of information uncertainty and subjectivity on the support and decision-making system; create a probabilistic entropy model to describe the state of the structure of the existing and prepared architecture; investigate the presence of bifurcation events and processes for the subsequent development of IT solutions. Creating a method for generating solution options involves building a sequence of events and processes related to the probabilistic content of the architecture and response to the state of the business process. The method is considered as the basis for the applicability of the architecture of IT solutions for generating a variety of probabilistic entropy states.
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