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A Utility Game Driven QoS Optimization for Cloud Services

delete2022-09-01
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PRE
AI
王
王燕 (Yan Wang) *
J
Jiantao Zhou
X
Xiaoyu Song
DOI:10.1109/TSC.2021.3062383delete
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摘要

摘要

En 中文
Cloud services request lower cost compared to traditional software of self-purchased infrastructure due to the characteristics of on-demand resource provisioning and pay-as-you-go mode. Current enterprises compact their business software as services into cloud platform to users. In the cloud services market, service providers attempt to make more profits from their services, while users hope to choose low-cost services with high-quality. The conflict of interests between users and service providers is an important challenge for the booming cloud service market. This article characterizes this application problem formally based on a utility game model of service providers and users. In the model, QoS is considered as the basis for determining the utilities of both parties from an economic point of view. By analyzing the behaviors of users and service providers, we introduce the concept of reputation cost for the first time in the model and find a QoS solution that balances the utilities of users and service providers in service transactions. In such a balance, any change in either party's strategy will result in a loss of utility. And then a QoS optimization method is designed to obtain a near-optimal QoS solution for a tradeoff between user satisfaction and provider profit. Extensive simulation experiments are conducted to substantiate the effectiveness of our method. The results are applicable to win-win service applications between service providers and users.
Keyword:
Quality of service
Games
Cloud computing
Optimization
Task analysis
Computational modeling
Economics
Cloud services
game
user preference
utility
QoS optimization
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期刊

IEEE Transactions on Services Computing 封面图
IEEE Transactions on Services Computing
IF:
5.8
论文数:
2.2K
被引数:
6.5K

机构

P
Portland State University
学者数:
3.3K
论文数: 3.3K
被引数: 5.0K
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Inner Mongolia University
学者数:
8.3K
论文数: 4.9K
被引数: 10
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