SARIMA Techniques for Predictive Resource Provisioning in Cloud Environments

Title

SARIMA Techniques for Predictive Resource Provisioning in Cloud Environments

Creator

Bhat C.R.; Prabha B.; Donald C.; Sah S.; Patil H.; Firos A.

Description

Seasonal Autoregressive Integrated Moving Average (SARIMA) models for dynamic cloud resource provisioning are introduced and evaluated in this work. Various cloud-based apps provided historical data to train and evaluate SARIMA models. The SARIMA(1,1,1)(0,1,1)12 model has an MAE of 0.056 and an RMSE of 0.082, indicating excellent prediction ability. This model projected resource needs better than other SARIMA settings. Sample prediction vs. real study showed close congruence between projected and observed resource consumption. MAE improved with hyperparameter adjustment, according to sensitivity analysis. Moreover, SARIMA-based resource allocation improved CPU usage by 12.5%, RAM utilization by 20%, and storage utilization by 21.4%. These data demonstrate SARIMA's ability to forecast cloud resource needs. SARIMA-based resource management might change dynamic cloud resource management systems due to cost reductions and resource usage efficiency. This research helps industry practitioners improve cloud-based service performance and cost. 2023 IEEE.

Source

2023 Intelligent Computing and Control for Engineering and Business Systems, ICCEBS 2023

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Cloud Environments; Predictive; Provisioning; Resource; SARIMA; Time Series Forecasting

Coverage

Bhat C.R., Saveetha School of Engineering (Saveetha Institute of Medical and Technical Sciences), Department of Computer Science and Engineering, Tamilnadu, Chennai, India; Prabha B., Loyola-ICAM College of Engineering and Technology, Department of It, Chennai, India; Donald C., CHRIST(Deemed to Be University), Department of Computer Science, Bengaluru, India; Sah S., School of Set, Sharda University, Greater Noida, India; Patil H., Computer Science and Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India; Firos A., Rajiv Gandhi University (A Central University)Rono-Hills, Department of Computer Science and Engineering, Arunachal Pradesh, Doimukh, India

Rights

Restricted Access

Relation

ISBN: 979-835039458-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICCEBS58601.2023.10449163

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189156755&doi=10.1109%2fICCEBS58601.2023.10449163&partnerID=40&md5=8403e06d74a978af6cfacd4333cad04d