Machine Learning-Based Task Allocation in Computational Networks

Авторы: Balashov Vasily, Plakunov Artem, Smeliansky Ruslan, Stepanov Evgeniy
Сборник: International Science and Technology Conference (Modern Networking Technologies) (MoNeTeC) 29-31 Oct. 2024
Год издания: 2024
Место издания: IEEE Moscow
DOI: 10.1109/MoNeTec60984.2024.10768108
Аннотация: Computational network (CN) is a set of computer nodes connected by a data transfer network and cooperatively processing a stream of incoming tasks (workload). Timely execution of tasks and balanced load of nodes are both required for CN operation. In this paper, we propose a machine learning-based multi-agent algorithm for task allocation to CN nodes. The convergence and solution quality of the algorithm are experimentally studied for different CN topologies and workloads. The algorithm requires splitting the CN into several domains with a dedicated agent in every domain. Influence of the number of domains on algorithm convergence is also experimentally studied.
Добавил в систему: Волканов Дмитрий Юрьевич

№	Имя	Описание	Имя файла	Размер	Добавлен
1.	Полный текст		Machine_Learning-Based_Task_Allocation_in_Computational_Net…	1,3 МБ	4 декабря 2024 [vbalashov]

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