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Fog Task Scheduling using Clustering based Randomized Round Robin
Author(s) -
Shahid Sultan Hajam,
Shabir Ahmad Sofi
Publication year - 2021
Publication title -
scalable computing. practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.192
H-Index - 18
ISSN - 1895-1767
DOI - 10.12694/scpe.v22i3.1891
Subject(s) - computer science , cluster analysis , scheduling (production processes) , distributed computing , round robin scheduling , fair share scheduling , real time computing , computer network , artificial intelligence , mathematical optimization , mathematics , quality of service
Fog computing serves the delay-sensitive applications of the Internet of Things (IoT) in more efficient means than the cloud. The heterogeneity of the tasks and the limited fog resources make task scheduling a complicated job. This paper proposes a clustering based task scheduling algorithm. Specifically, the K-Means++ clustering algorithm is used for clustering the fog nodes. Randomized round robin, a task scheduling algorithm is applied to each cluster. The results show that the proposed algorithm reduces the system's average waiting time.

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