QoS-Aware Algorithm Based on Task Flow Scheduling in Cloud Computing Environment

Mohamed Ali Rakrouki; Nawaf Alharbe

doi:10.3390/s22072632

QoS-Aware Algorithm Based on Task Flow Scheduling in Cloud Computing Environment

Sensors (Basel). 2022 Mar 29;22(7):2632. doi: 10.3390/s22072632.

Authors

Mohamed Ali Rakrouki^{1

2

3}, Nawaf Alharbe¹

Affiliations

¹ Applied College, Taibah University, Medina 42353, Saudi Arabia.
² Ecole Supérieure des Sciences Economiques et Commerciales de Tunis, University of Tunis, Montfleury 1089, Tunisia.
³ Business Analytics and DEcision Making Lab (BADEM), Tunis Business School, University of Tunis, Bir El Kassaa 2059, Tunisia.

Abstract

This paper deals with the challenging problem of scheduling users' tasks, while taking into consideration users' quality of service (QoS) requirements, with the objective of reducing the energy consumption of physical machines. This paper presents a model to analyze the current state of the running tasks according to the results of the QoS prediction assigned by an ARIMA prediction model optimized with Kalman filter. Then, we calculate a scheduling policy with a combined particle swarm optimization (PSO) and gravitational search algorithm (GSA) algorithms according to the QoS status analysis. Experimental results show that the proposed HPSO algorithm reduces resources consumption 16.51% more than the original hybrid algorithm, and the violation of service-level agreement (SLA) is 0.053% less when the optimized prediction model is used.

Keywords: ARIMA; QoS; cloud computing; scheduling; virtual machine placement.

MeSH terms

Algorithms*
Cloud Computing*
Gravitation