Improving the Processing Speed of Task Scheduling in Cloud Computing Using the Resource Aware Scheduling Algorithm over the Max-Min Algorithm

P. Priya, S. Thanjaraj

2023

Abstract

The study aimed to bolster the efficiency of task scheduling in cloud computing through the novel Resource Aware Scheduling Algorithm (RASA) and contrasted its performance with the Max-Min Algorithm. Cloud computing, with its decentralised nature, distributes internet-based resources, handling a diverse array of demands. For this research, data for task scheduling was sourced from the Cloudsim Tool. The cloud infrastructure was analysed, designed, and implemented to test both RASA and the Max-Min Algorithm, utilising 120 samples in two distinct groups. The processing speed outcomes, analysed via IBM SPSS, showed RASA to be notably superior. The independent sample t-test had a significance of 0.007(p < 0.05), highlighting the distinctiveness of the algorithms. Impressively, RASA's processing speed outstripped that of the Max-Min Algorithm.

Paper Citation

in Harvard Style

Priya P. and Thanjaraj S. (2023). Improving the Processing Speed of Task Scheduling in Cloud Computing Using the Resource Aware Scheduling Algorithm over the Max-Min Algorithm. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 589-594. DOI: 10.5220/0012544200003739

in Bibtex Style

@conference{ai4iot23,
author={P. Priya and S. Thanjaraj},
title={Improving the Processing Speed of Task Scheduling in Cloud Computing Using the Resource Aware Scheduling Algorithm over the Max-Min Algorithm},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={589-594},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012544200003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Improving the Processing Speed of Task Scheduling in Cloud Computing Using the Resource Aware Scheduling Algorithm over the Max-Min Algorithm
SN - 978-989-758-661-3
AU - Priya P.
AU - Thanjaraj S.
PY - 2023
SP - 589
EP - 594
DO - 10.5220/0012544200003739
PB - SciTePress