SELF-LEARNING OF PARAMETER WEIGHTS FOR TASK SCHEDULING IN GRID COMPUTING ENVIRONMENT

Authors

  • Donatas Sandonavičius Kaunas University of Technology
  • AuÅ¡ra GadeikytÄ— Kaunas University of Technology
  • Giedrius Paulikas Kaunas University of Technology
  • Mindaugas VaitkÅ«nas Kaunas University of Technology
  • Gytis Vilutis Kaunas University of Technology
  • Gintaras Butkus Kaunas University of Applied Sciences

Keywords:

Grid, Cloud, Quality of Service, Resource Broker, Self-learning of parameter weights

Abstract

The Grid computing environment is very important for solving scientific problems. To get the best performance from Grid, it is important to know where to send tasks. This paper is about one of the suggested methods for a Grid resource broker to find the best resources for the task. This method requires defining the parameters of the resources and knowing the importance of the weights of parameters. This paper also presents the self-learning method of parameter weights.

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Published

2021-12-09

Issue

Vol. 2 No. 17 (2021): Mokslo taikomieji tyrimai Lietuvos kolegijose

Section

Technologijos mokslų tyrimai

How to Cite

SELF-LEARNING OF PARAMETER WEIGHTS FOR TASK SCHEDULING IN GRID COMPUTING ENVIRONMENT. (2021). Mokslo Taikomieji Tyrimai Applied Research, 2(17), 123-129. http://5.133.66.111/index.php/mttlk/article/view/503

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