Search

Networked interconnected systems are often deployed in infrastructures with resource allocation using isolated virtual environments. The technological implementation of such systems varies significantly, making it difficult to accurately estimate the required volume of resources to allocate for each virtual environment. This leads to overprovisioning of some services and underprovisioning of others. The problem of distributing the available computational resources between the system services arises. To efficiently use resources and reduce resource waste, the problem of minimizing free resources under conditions of unknown ratios of resource distribution between services is formalized; an approach to determining regression dependencies of computing resource consumption by services on the number of requests and a procedure for efficient resource distribution between services are proposed. The proposed solution is experimentally evaluated using the networked interconnected system model. The results show an increase in throughput by 20.75% compared to arbitrary resource distribution and a reduction in wasted resources by 55.59%. The dependences of the use of resources by networked interconnected system services on the number of incoming requests, identified using the proposed solution, can also be used for scaling in the event of an increase in the total volume of allocated resources. [ABSTRACT FROM AUTHOR]

A web platform for psychological research needs a single format of questionnaire tests to ensure interaction between its components. The study proposes a general test structure, variant questions, variations in response types, and an embedded domain-specific language for computations. The use of JSON is proposed and justified to store the hierarchical structure of the questionnaire test, and JSON Schema is defined as a technology suitable for the formation of the standard. From the considered validation instruments for compliance with the standard described in JSON Schema, ajv was defined as the most applicable to the task. To build the documentation, Doca is relevant, but this tool needs to be modified to meet the requirements of the task.

Predictive learning services perform aggregation and homogenization of open data from public sources, in particular from the online recruitment agencies. However, the sample of vacancies may contain various percentage of noise due to the frequent occurrence of homonyms. This article will consider two approaches of noise reduction: the first one is based on the cosine similarity and the second one is based on the contextual words.

This article is devoted to contemporary methods of risk management under the conditions of crisis on financial markets. The article deals with developing the new approaches to studying finance and financial markets. It outlays new methods to compare fundamental events and their technical interpretation shown on quotation charts. It also introduces recommendations as to improve the risk management’s efficiency of financial markets’ participants.

At the present time the technology market is constantly growing, new technologies emerge every day so it makes it hard to track all of them and evaluate their potential. As the retraining process takes significant time, the acute need to change the staff training approach from reactive to proactive arises. There are services for monitoring and modeling purposes developed by Quid, Owlin, Djinni. Another approach is the expert analysis. But every of the defined information sources has its drawbacks, which leads to a decision to develop a software and mathematical solution. The article suggests methods of skills demand monitoring for the IT sector, based on comprehensive monitoring of the Web, including employers’ demands, company history and publications.

The paper shows an experimental approach to the selection of a set of software components based on computational experiments simulating the desired operating conditions of the software system being developed. A mathematical model is constructed, aimed at an effective selection of components from the available alternative options. The model and process of components selection are introduced and applied to the case of selecting Node.js components for the development of the Digital Psychological Tools for Conducting the Large-Scale Psychological Research. The aim of the platform development is to facilitate the countrywide simultaneous online psychological surveys in schools in the conditions of unstable Internet connection and the large variety of desktop and mobile client devices, running different operating systems and browsers. The module, which development is considered in the paper, should provide the functionality for archiving and checksum verification of the survey forms and graphical data. With the experimental approach proposed in the paper, the effective set of components was identified based on evaluations of 14 quality of operation indicators. To simulate the desired operating conditions and to guarantee the reproducibility of the experiments, the virtual infrastructure was configured, and the genetic algorithm was applied to reduce the number of experiments with the unpromising sets of software components. The application of the genetic algorithm led to the reproducible results of components selection after 220 experiments instead of 1080 experiments needed by the exhaustive search algorithm. The suggested approach can be widely used for effective selection of software components for distributed systems operating in the given conditions at the stage of their development. [ABSTRACT FROM AUTHOR]