Almomani, A, Igried, Bashar, Alsarhan, Ayoub and Alauthman, Mohammad (2022) Machine learning Scheme for Managing Virtual Computing Resources in Cloud Market. In: 2022 International Arab Conference on Information Technology (ACIT), 22-24 November 2022, Abu Dhabi, United Arab Emirates.
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Cloud provider can maximize his profit while guaranteeing quality of service (QoS) required by clients. In this work, we propose new scheme for maximizing cloud provider profit while guaranteeing QoS for clients. Cloud provider (CP) manages all available resources on cloud market. The key objective of our scheme is extracting the optimal charging strategy for serving clients requests to maximize CP's profit by choosing proper set of requests to be served, subject to uncertain demand of service and time-varying service cost. As variety of clients classes submit their requests and offer different prices for service, this problem deserves special treatment. To tackle the uncertain service prices, Q-Iearning is proposed to extract the optimal charging policy. Numerical results show that the proposed scheme can improve the reward of CP significantly.
Affiliation: | Skyline University College |
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SUC Author(s): | Almomani, A ORCID: https://orcid.org/0000-0002-8808-6114 |
All Author(s): | Almomani, A, Igried, Bashar, Alsarhan, Ayoub and Alauthman, Mohammad |
Item Type: | Conference or Workshop Item (Paper) |
Uncontrolled Keywords: | Cloud computing, Costs, Quality of service, Machine learning, Information technology |
Subjects: | B Information Technology > BB Information Technology B Information Technology > BL Machine Learning B Information Technology > BV Cloud Computing |
Divisions: | Skyline University College > School of IT |
Depositing User: | Mr Mosys Team |
Date Deposited: | 26 Jan 2024 15:00 |
Last Modified: | 26 Jan 2024 15:00 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/775 |
Publisher URL: | https://doi.org/10.1109/ACIT57182.2022.9994186 |
Publisher OA policy: | |
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