A Resource Allocation Scheme with the Best Revenue in the Computing Power Network
The emergence of computing power networks has improved the flexibility of resource scheduling. Considering the current trading scenario of computing power and network resources, most resources are no longer subject to change after being allocated to users until the end of the lease. However, this pr...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/9/1990 |
| _version_ | 1797602757635473408 |
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| author | Zuhao Wang Yanhua Yu Di Liu Wenjing Li Ao Xiong Yu Song |
| author_facet | Zuhao Wang Yanhua Yu Di Liu Wenjing Li Ao Xiong Yu Song |
| author_sort | Zuhao Wang |
| collection | DOAJ |
| description | The emergence of computing power networks has improved the flexibility of resource scheduling. Considering the current trading scenario of computing power and network resources, most resources are no longer subject to change after being allocated to users until the end of the lease. However, this practice often leads to idle resources during resource usage. To optimize resource allocation, a trading mechanism is needed to encourage users to sell their idle resources. The Myerson auction mechanism precisely aims to maximize the seller’s benefits. Therefore, we propose a resource allocation scheme based on the Myerson auction. In the scenario of the same user bidding distribution, we first combine the Myerson auction with Hyperledger Fabric by introducing a reserved price, which creates conditions for the application of blockchain in auction scenarios. Regarding different user bidding distributions, we propose a Myerson auction network model based on clustering algorithms, which makes the auction adaptable to more complex scenarios. The experimental findings show that the revenue generated by the auction model in both scenarios is significantly higher than that of the traditional sealed bid second-price auction, and can approach the expected revenue in the real Myerson auction scenario. |
| first_indexed | 2024-03-11T04:21:09Z |
| format | Article |
| id | doaj.art-6964d2f755fe47e5a7d97a8c8bd336b9 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T04:21:09Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-6964d2f755fe47e5a7d97a8c8bd336b92023-11-17T22:47:13ZengMDPI AGElectronics2079-92922023-04-01129199010.3390/electronics12091990A Resource Allocation Scheme with the Best Revenue in the Computing Power NetworkZuhao Wang0Yanhua Yu1Di Liu2Wenjing Li3Ao Xiong4Yu Song5State Key Laboratory of Network and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Network and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Grid Information & Telecommunications Group Co., Ltd., Beijing 102209, ChinaState Grid Information & Telecommunications Group Co., Ltd., Beijing 102209, ChinaState Key Laboratory of Network and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Network and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe emergence of computing power networks has improved the flexibility of resource scheduling. Considering the current trading scenario of computing power and network resources, most resources are no longer subject to change after being allocated to users until the end of the lease. However, this practice often leads to idle resources during resource usage. To optimize resource allocation, a trading mechanism is needed to encourage users to sell their idle resources. The Myerson auction mechanism precisely aims to maximize the seller’s benefits. Therefore, we propose a resource allocation scheme based on the Myerson auction. In the scenario of the same user bidding distribution, we first combine the Myerson auction with Hyperledger Fabric by introducing a reserved price, which creates conditions for the application of blockchain in auction scenarios. Regarding different user bidding distributions, we propose a Myerson auction network model based on clustering algorithms, which makes the auction adaptable to more complex scenarios. The experimental findings show that the revenue generated by the auction model in both scenarios is significantly higher than that of the traditional sealed bid second-price auction, and can approach the expected revenue in the real Myerson auction scenario.https://www.mdpi.com/2079-9292/12/9/1990resource allocationauction mechanismblockchaindeep learningclustering algorithm |
| spellingShingle | Zuhao Wang Yanhua Yu Di Liu Wenjing Li Ao Xiong Yu Song A Resource Allocation Scheme with the Best Revenue in the Computing Power Network Electronics resource allocation auction mechanism blockchain deep learning clustering algorithm |
| title | A Resource Allocation Scheme with the Best Revenue in the Computing Power Network |
| title_full | A Resource Allocation Scheme with the Best Revenue in the Computing Power Network |
| title_fullStr | A Resource Allocation Scheme with the Best Revenue in the Computing Power Network |
| title_full_unstemmed | A Resource Allocation Scheme with the Best Revenue in the Computing Power Network |
| title_short | A Resource Allocation Scheme with the Best Revenue in the Computing Power Network |
| title_sort | resource allocation scheme with the best revenue in the computing power network |
| topic | resource allocation auction mechanism blockchain deep learning clustering algorithm |
| url | https://www.mdpi.com/2079-9292/12/9/1990 |
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