Adaptive Preventive and Remedial Measures in Resolving Cloud Quality of Service Violation


Chua, Fang Fang and Chan, Gaik Yee and Wong, Tong Sheng (2019) Adaptive Preventive and Remedial Measures in Resolving Cloud Quality of Service Violation. In: 33rd International Conference on Information Networking, ICOIN 2019, 9-11 Jan. 2019, Kuala Lumpur, Malaysia.

[img] Text
198.pdf - Published Version
Restricted to Repository staff only

Download (947kB)


Cloud Computing acts as a paradigm to support on-demand computing services, from applications to storage, manage and processing capabilities. One of the major challenges in delivering and accessing cloud applications is the management of Quality of Service (QoS) and cloud service providers are mandated to adhere to Service Level Agreement (SLA) in providing quality cloud services to the users. The agreement matching is important for both parties to ensure satisfaction and expectation level. This proposed work aims to resolve cloud QoS violation with the implementation of adaptive preventive and remedial mechanisms. Preventive measure such as horizontal scaling is used to optimize the performance of a running cloud service in order to prevent the cloud service to downgrade to QoS violation condition. Remedial action on the other hand, is to provide fault tolerance using replication for faulty cloud service to recover from failure incidents or already violation condition. Experimental results have demonstrated the feasibility and effectiveness of applying horizontal scaling in preventing and replication in rectifying cloud QoS violations based on response time and throughput.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Cloud Computing
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 07 Jan 2022 02:29
Last Modified: 07 Jan 2022 02:29


Downloads per month over past year

View ItemEdit (login required)