Nowadays, simulation modeling is a relevant and practically significant means in the field for research of infrastructure object functioning. It forms the basis for studying the most important components of such objects represented by their digital twins. Applying meteorological data, in this context, becomes an important issue. In the paper, we propose a new microservice-based approach for organizing simulation modeling in heterogeneous distributed computing environments. Within the proposed approach, all operations related to data preparing, executing models, and analyzing the obtained results are implemented as microservices. The main advantages of the proposed approach are the parameter sweep computing within simulation modeling and possibility of integrating resources of public access supercomputer centers with cloud and fog platforms. Moreover, we provide automated microservice web forms using special model specifications. We develop and apply the service-oriented tools for studying environmentally friendly equipment of the objects at the Baikal natural territory. Among such objects are recreation tourist centers, children’s camps, museums, exhibition centers, etc. As a result, we have evaluated the costs for the possible use of heat pumps in different operational and meteorological conditions for the typical object. The provided comparative analysis has confirmed the aforementioned advantages of the proposed approach.

National economy digitalization is a powerful economic growth engine and one of the key areas for developing and maintaining the competitiveness of the state. Digital economy potential lies in accelerating the pace of economic development of enterprises, industries, regions and countries, and in improving in living standards. Under the conditions of digitalization, a tool for assessing the pace of economic system development at the country, region, industry and enterprise level becomes a source of competitive advantages. Therefore, the relevance of the study is evident. The purpose of the study is to develop tools for studying digital development rates at country and region level. The database of the study was represented by the proceeding of well-known foreign and Russian scientists and statistical data on the main indices of the US and Chinese stock markets. The methodological base was represented by the ISPI (Information System Portfolio Investor) digital model. The effectiveness of the obtained results was verified using the PRM (Profitability-Risk model) tool. The result of the study was an analysis of digital development rates at the country level by the case of the United States and China. The analysis was based on the calculation of the main parameters of the portfolio theory: expected return, risk level, return-to-risk ratio. Scatterplots were constructed for the main US and Chinese stock market indices based on the fitted data. They show the mutual distribution of groups of main indices and allow to determine the most promising areas for investment, including digital development. The findings confirm the possibility of using the proposed tools to determine the most attractive sectors for investment in the world stock markets and countries, and/or countries and regions that need investment for their development, including digital one. The introduction of the proposed tools into practice at the enterprise, industry, region and country level will contribute to the further development of the digitalization in all aspects of society at the enterprise, industry, region and country level.

The paper addresses an important problem related to automation of simulation modeling of queue systems using high-performance computing. There is a large spectrum of tools for the simulation modeling of such systems. However, these tools often do not use the possibilities of subject-oriented high-performance computing in full. The purpose of the study is the development of the new tools for automation of the simulation modeling of queue systems in a heterogeneous distributed computing environment. To this end, we develop specialized applications for parameter sweep computations in such an environment. A methodology of the application development is based on the integrated use of methods of the conceptual and wireframe programming, methods of the computations planning and resources allocation, methods of parameter sweep computations, and methods of the data analysis. We develop the toolkit named SIRIUS III for the simulation modeling of queue systems using high-performance computing. In addition, we design a conceptual model that represents knowledge about both the subject domain of solved problems and computing environment. Using the proposed toolkit, we solved a number of problems related to warehouse logistics. Computational experiments showed the high scalability of parameter sweep computations on heterogeneous resources.

The paper addresses a relevant problem of predicting the runtime of jobs for executing problem-solving schemes of large-scale applications in a heterogeneous distributed computing environment. Such an environment includes nodes that have various hardware architectures, different system software, and diverse computational possibilities. We believe that increasing the accuracy in predicting the runtime of jobs can significantly improve the efficiency of problem-solving and rational use of resources in the heterogeneous environment. To this end, we propose new models that make it possible to take into account various estimations of the module runtime for all modules included in the problem-solving scheme. These models were developed using the special computational model of distributed applied software packages (large-scale scientific applications). In addition, we compare the prediction results (jobs runtime and their errors) using different estimations. Among them are the estimations obtained through the modules testing, users estimations, and estimations based on computational history. These results were obtained in continuous integration, delivery, and deployment of applied and system software of a package for solving warehouse logistics problems. They show that the largest accuracy is achieved by the modules testing.