Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information

In order to deal with the problem of user diversity in Mobile Edge Computing (MEC) resource trading market, in this paper, we propose a hybrid market-based resource transaction mechanism consisting of futures market and spot market. Two different types of users have been taken into consideration. On...

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Main Authors: Huang, Xiaowen, Gong, Shimin, Yang, Jingmin, Zhang, Wenjie, Yang, Liwei, Yeo, Chai Kiat
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/159752
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1597522022-07-01T05:52:39Z Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information Huang, Xiaowen Gong, Shimin Yang, Jingmin Zhang, Wenjie Yang, Liwei Yeo, Chai Kiat School of Computer Science and Engineering Engineering::Computer science and engineering Resources Allocation Mobile Edge Computing In order to deal with the problem of user diversity in Mobile Edge Computing (MEC) resource trading market, in this paper, we propose a hybrid market-based resource transaction mechanism consisting of futures market and spot market. Two different types of users have been taken into consideration. One is registered users and another is unregistered users. In futures market, registered users pay a registration fee to the agent and use the reserved resources according to the contract signed exclusively. We design optimal contracts for the registered users by adjusting the registration fee in order to maximize the servers’ utility. In spot market, unregistered users compete with one another to purchase the resources on demand. We model the trading process as a multi-seller and multi-buyer market, and propose auction algorithms to match the asking price from servers and the bidding price from unregistered users by assigning computation resources to the users. The agent acts as the auctioneer to host the auction, and the unregistered users bid on computation resources based on the estimated valuation. We study the optimal solution under both complete and incomplete information scenarios, depending on whether the agent can observe the users’ private information. Simulation results demonstrate the existences of the asking price and registration fee for the servers to maximize utility. This work is supported by Natural Science Funds of China (Nos. 61701213, 61705260), and Natural Science Funds of Fujian, China (No. 2018J01546, 2020J01813). 2022-07-01T05:52:38Z 2022-07-01T05:52:38Z 2022 Journal Article Huang, X., Gong, S., Yang, J., Zhang, W., Yang, L. & Yeo, C. K. (2022). Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information. Future Generation Computer Systems, 127, 80-91. https://dx.doi.org/10.1016/j.future.2021.08.029 0167-739X https://hdl.handle.net/10356/159752 10.1016/j.future.2021.08.029 2-s2.0-85114998906 127 80 91 en Future Generation Computer Systems © 2021 Elsevier B.V. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Resources Allocation
Mobile Edge Computing
spellingShingle Engineering::Computer science and engineering
Resources Allocation
Mobile Edge Computing
Huang, Xiaowen
Gong, Shimin
Yang, Jingmin
Zhang, Wenjie
Yang, Liwei
Yeo, Chai Kiat
Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information
description In order to deal with the problem of user diversity in Mobile Edge Computing (MEC) resource trading market, in this paper, we propose a hybrid market-based resource transaction mechanism consisting of futures market and spot market. Two different types of users have been taken into consideration. One is registered users and another is unregistered users. In futures market, registered users pay a registration fee to the agent and use the reserved resources according to the contract signed exclusively. We design optimal contracts for the registered users by adjusting the registration fee in order to maximize the servers’ utility. In spot market, unregistered users compete with one another to purchase the resources on demand. We model the trading process as a multi-seller and multi-buyer market, and propose auction algorithms to match the asking price from servers and the bidding price from unregistered users by assigning computation resources to the users. The agent acts as the auctioneer to host the auction, and the unregistered users bid on computation resources based on the estimated valuation. We study the optimal solution under both complete and incomplete information scenarios, depending on whether the agent can observe the users’ private information. Simulation results demonstrate the existences of the asking price and registration fee for the servers to maximize utility.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Huang, Xiaowen
Gong, Shimin
Yang, Jingmin
Zhang, Wenjie
Yang, Liwei
Yeo, Chai Kiat
format Article
author Huang, Xiaowen
Gong, Shimin
Yang, Jingmin
Zhang, Wenjie
Yang, Liwei
Yeo, Chai Kiat
author_sort Huang, Xiaowen
title Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information
title_short Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information
title_full Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information
title_fullStr Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information
title_full_unstemmed Hybrid market-based resources allocation in Mobile Edge Computing systems under stochastic information
title_sort hybrid market-based resources allocation in mobile edge computing systems under stochastic information
publishDate 2022
url https://hdl.handle.net/10356/159752
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