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Multi-agent Model of Resource Allocation in Distributed Computing Environment for Job Flow Processing

Авторы: Kostromin R., Feoktistov A.

Журнал: Proceedings of ITNT 2020: 6th IEEE Intern. Conf. on Information Technology and Nanotechnology (ITNT 2020; Samara, 26-29 May 2020)

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Год: 2020

Отчётный год: 2020

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DOI: 10.1109/ITNT49337.2020.9253215

Аннотация: Currently, a resource allocation issue in a high-performance computing environment is still a challenge. Its solution enables us to improve large spectrum criteria. Among them are the time, cost, reliability and other parameters of problem-solving by end-users. High computational complexity related to optimal solving this issue through the hard search among all scenarios of the resource allocation. At the same time, we can apply knowledge-based heuristic approaches to obtain satisfactory sub-optimal solutions. Applying a multi-agent technology is one such approach. In the paper, we propose a multi-agent model of resource allocation in a high-performance computing environment in the job flow processing. We suppose that such job flows are generated by distributed applied software package. A high-performance computing environment is based on the resources of a public access supercomputer center. In such conditions, we compare traditional meta-schedulers (GridWay and Condor DAGMan) and our multi-agent system in terms of the effectiveness of job flow management. We provide the experimental results that obviously show advantages of the proposed multi-agent management in speedup and efficiency of computations, processor load, and its balancing.

Индексируется WOS: Q5

Индексируется Scopus: Нет

Индексируется УБС: Нет

Индексируется РИНЦ: Да

Индексируется ВАК: Нет

Индексируется CORE: Нет

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