Preventing and Rectifying Cloud Quality of Service Violation Through Adaptive Resource Scaling and Replication

Citation

Wong, Tong Sheng and Chan, Gaik Yee and Chua, Fang Fang (2019) Preventing and Rectifying Cloud Quality of Service Violation Through Adaptive Resource Scaling and Replication. International Journal of Technology, 10 (7). pp. 1395-1406. ISSN 2086-9614

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Abstract

One major challenge in delivering and accessing cloud applications is the management of Quality of Services (QoS). It is mandatory for cloud service providers to ensure their performance and fulfil QoS, as defined in the Service Level Agreement (SLA). In this paper, we propose a Scaling and Fault Tolerance (SFT) algorithm to deploy preventive or remedial measures based on 16 decision rules for QoS violation detection and prediction. We simulate the SFT algorithm in a cloud simulator with four scenarios to measure its effectiveness in handling events such as faulty virtual machines (VMs), or over and under-provisioning of resources. Our experimental results show that the proposed SFT algorithm performs effectively (close to a 90%100% effective rate) in providing preventive or remedial measures and reducing the number of VMs when they are not needed.

Item Type: Article
Uncontrolled Keywords: Cloud computing; Fault tolerance; Quality of service violation; Replication; Scalability
Subjects: Q Science > QC Physics > QC770-798 Nuclear and particle physics. Atomic energy. Radioactivity
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 28 Oct 2021 02:40
Last Modified: 28 Oct 2021 02:40
URII: http://shdl.mmu.edu.my/id/eprint/8878

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