A Fair Scheduling Algorithm for Multiprocessor Systems Using a Task Satisfaction Index

With the emergence of increasingly heterogeneous devices and networks, computing systems are required to support a variety of services with different quality of service requirements. The degree of heterogeneity makes it more difficult 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.