A Fair Scheduling Algorithm for Multiprocessor Systems Using a Task Satisfaction Index.
Journal
Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017
Journal Volume
2017-January
Pages
269-274
Date Issued
2017
Author(s)
Abstract
With the emergence of increasingly heterogeneous devices and networks, computing systems are required to support a variety of services with difierent quality of service requirements. The degree of heterogeneity makes it more dificult to fairly allocate resources based on the client's weight. Moreover, as the systems become larger, their performance can worsen significantly. In this paper, we present a fair scheduling algorithm for multiprocessor systems using a task satisfaction index. The proposed algorithm, called LZF, aims to achieve a high level of proportional fairness for the heterogeneous tasks. The evaluation results show that its service time error is bounded between -1 and 1, and the LZF achieves the best proportional fairness among existing scheduling algorithms with respect to the average service time error. © 2017 Association for Computing Machinery.
Subjects
CPU scheduling; Fairness; Proportional share scheduling; Quality of Service; Resource managements
SDGs
Other Subjects
Multiprocessing systems; Quality of service; Scheduling; Telecommunication services; CPU scheduling; Fair scheduling algorithm; Fairness; Heterogeneous devices; Multi processor systems; Proportional fairness; Proportional-share; Resource management; Scheduling algorithms
Type
conference paper