Open AccessMULTIAGENT METHODS OF MANAGEMENT OF DISTRIBUTED COMPUTING IN HYBRID CLUSTERS
Author(s) -
Vadim Kolumbet,
Olha Svynchuk
Publication year - 2022
Publication title -
sučasnì ìnformacìjnì sistemi
Language(s) - English
Resource type - Journals
ISSN - 2522-9052
DOI - 10.20998/2522-9052.2022.1.05
Subject(s) - computer science , distributed computing , grid computing , scalability , grid , adaptability , end user computing , virtualization , task management , resource management (computing) , distributed design patterns , utility computing , computer cluster , semantic grid , task (project management) , cloud computing , distributed algorithm , database , operating system , systems engineering , artificial intelligence , ecology , semantic web , geometry , mathematics , engineering , biology , cloud computing security
Modern information technologies include the use of server systems, virtualization technologies, communication tools for distributed computing and development of software and hardware solutions of data processing and storage centers, the most effective of such complexes for managing heterogeneous computing resources are hybrid GRID- distributed computing infrastructure combines resources of different types with collective access to these resources for and sharing shared resources. The article considers a multi-agent system that provides integration of the computational management approach for a cluster Grid system of computational type, the nodes of which have a complex hybrid structure. The hybrid cluster includes computing modules that support different parallel programming technologies and differ in their computational characteristics. The novelty and practical significance of the methods and tools presented in the article are a significant increase in the functionality of the Grid cluster computing management system for the distribution and division of Grid resources at different levels of tasks, the ability to embed intelligent computing management tools in problem-oriented applications. The use of multi-agent systems for task planning in Grid systems will solve two main problems - scalability and adaptability. The methods and techniques used today do not sufficiently provide solutions to these complex problems. Thus, the scientific task of improving the effectiveness of methods and tools for managing problem-oriented distributed computing in a cluster Grid system, integrated with traditional meta-planners and local resource managers of Grid nodes, corresponding to trends in the concept of scalability and adaptability.