Algorithms for Solution Inference Based on Unified Logical Control Models

Litvinenko, A. E.

doi:10.1007/s10559-020-00234-9

Cited by 2 publications

(1 citation statement)

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“…Each of the microservices is located on a separate virtual server, which receives the necessary resource in accordance with the general principles of load balancing on the system. The load balancing module is configured at the server core le vel and provides for the use of decisionmaking algorithms based on the state of the system [12][13][14] according to the following input parameters: type of protocols for network balancing. The research was conducted on the same type of training courses (100 training courses, among which were experi mental courses for training UAV pilots (unmanned aerial vehicle) [15,16]).…”

Section: 2mentioning

confidence: 99%

Use analysis of microserves in e-learning system with multi-variant access to educational materials

Artamonov

Golovach²,

Zymovchenko

2021

TAPR

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The object of research is the electronic learning system. The subject of the research is the method of using microservices in the construction of online systems. One of the most problematic areas in the development of high-load online systems is the coordination of all microservices in a single system and the distribution of the load on hardware resources at critical indicators of system utilization. This leads to the complication of the process of development, implementation and operation of the training system, as well as high requirements for the personnel who will support the operation of the system. In the research, during the transition from the monolithic architecture of the e-learning system to the microservice architecture, the main indicators of the server hardware and the average response time to user requests were monitored. These indicators were fundamental when setting up the system as a whole and balancing the load during its operation. The proposed method for the implementation of the system can significantly reduce the hardware requirements and reduce the response time of the system under high load conditions (from 10,000 unique users per unit of time). Also, this method greatly simplifies the development and modification of online systems that use a large number of different user roles and differentiation of levels of access to the system. The obtained results of the approbation of the method allow to consider it an effective tool for the development of online learning systems with multivariate access to educational materials. Unlike existing monolithic architects, the proposed method allows to manage system resources and apply new settings without rebooting, which allows to ensure the continuity of system operation. As a justification for this method, options for the implementation of online training systems and load balancing settings are proposed. The management of load balancing in the microservice architecture of the implementation of online systems is based on the analysis of the load indicators of processor cores and the use of RAM by system services.

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Section: 2mentioning

confidence: 99%