Title: Smart resource scheduling by correlating discriminative quality factors to optimise resource utilisation in IAAS of cloud networks

Authors: Bellam Ravindra Babu; Aliseri Govardhan

Addresses: Jawaharlal Nehru Technological University Hyderabad JNTUH, Hyderabad, Telangana, 500085, India ' Jawaharlal Nehru Technological University Hyderabad JNTUH, Hyderabad, Telangana, 500085, India

Abstract: The significant requirement in cloud computing is detecting the deterministic model for performing resource scheduling. Resource scheduling is crucial because of the presence of several anomalies and high dimensionality values shown during resource scheduling. The number of tasks envisioned in contention at resource broker of IAAS and higher dimensionality of proposed anomalies values for quality resource aspects was out of scope concerning the existing resource scheduling techniques. Therefore, the contemporary resource scheduling techniques were not prominent for optimal resource scheduling. For optimising resource scheduling in terms of earlier mentioned properties like the maximum amount of tasks and maximum dimensionality anomalies projection, an ensemble resource scheduling technique has been derived in this article under batch scheduling classification. Further, the simulation study envisioned that the projected model of this contribution is more significant and robust for delivering optimum resource scheduling when compared to other contemporary models in terms of dimensionality and volume of anomalies.

Keywords: resource scheduling; VM migration; virtual machines; VMs; QoS; cloud computing; resource management.

DOI: 10.1504/IJEB.2022.126250

International Journal of Electronic Business, 2022 Vol.17 No.4, pp.319 - 335

Received: 12 Jan 2021
Accepted: 27 May 2021
Published online: 18 Oct 2022 *

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