Hierarchical Reverse Games for the Resource Ecosystem in Cloud–Edge Computing

Edge computing has emerged as a killer technology for a hyper-connected world due to its distributed architecture and customer-proximity property. Combined edge nodes with the cloud data center, a cloud-edge computing paradigm is formed, whose resource ecosystem calls for competitive pricing and optimal resource allocation. However, it is not feasible to realize global information-based optimization since some information is kept private to their owners. To solve this challenge, this paper develops the user-independent hierarchical reverse game and the user-assisted hierarchical reverse game to depict the relationship among the resource provider, the resource tenant, and the resource user. The aim is to seek the optimal strategies for players without revealing any private information. The common trait of both games is to force the players to report the optimal strategies based on their actual private information. This salient trait can produce privacy-preservation optimization since there is no requirement for the players to release their individual information directly, and the optimal strategies of other players can be deduced naturally. The difference between the user-independent hierarchical reverse game and the user-assisted one is that the game rules are stipulated entirely by the provider and the tenants (edge nodes) in the former, while some game rules can be customized according to the advice of users in the latter. This leads the user-independent hierarchical reverse game is more concise and easy to guarantee the incentive compatibility constraint, while the user-assisted hierarchical reverse game can attract more users since the game rules can adapt to their economic status, requirements, and preferences.

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Publication Details

Journal
IEEE Transactions on Consumer Electronics
Published
2024-08-21
DOI
https://doi.org/10.1109/tce.2024.3415572
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Hierarchical Reverse Games for the Resource Ecosystem in Cloud–Edge Computing

Zhigao Zheng, Shengling Wang, Yufei Guo, Manlin Pei et al.
IEEE Transactions on Consumer Electronics
Distributed and Parallel Computing Systems
article

Hierarchical Reverse Games for the Resource Ecosystem in Cloud–Edge Computing

Zhigao Zheng, Shengling Wang, Yufei Guo, Manlin Pei, Chenyu Wang, Xia Wang, Jianhui Huang
article en

Abstract

Edge computing has emerged as a killer technology for a hyper-connected world due to its distributed architecture and customer-proximity property. Combined edge nodes with the cloud data center, a cloud-edge computing paradigm is formed, whose resource ecosystem calls for competitive pricing and optimal resource allocation. However, it is not feasible to realize global information-based optimization since some information is kept private to their owners. To solve this challenge, this paper develops the user-independent hierarchical reverse game and the user-assisted hierarchical reverse game to depict the relationship among the resource provider, the resource tenant, and the resource user. The aim is to seek the optimal strategies for players without revealing any private information. The common trait of both games is to force the players to report the optimal strategies based on their actual private information. This salient trait can produce privacy-preservation optimization since there is no requirement for the players to release their individual information directly, and the optimal strategies of other players can be deduced naturally. The difference between the user-independent hierarchical reverse game and the user-assisted one is that the game rules are stipulated entirely by the provider and the tenants (edge nodes) in the former, while some game rules can be customized according to the advice of users in the latter. This leads the user-independent hierarchical reverse game is more concise and easy to guarantee the incentive compatibility constraint, while the user-assisted hierarchical reverse game can attract more users since the game rules can adapt to their economic status, requirements, and preferences.

IEEE Transactions on Consumer ElectronicsVol. 71(2)
Kennesaw State University (US), Georgia State University (US), George Washington University (US), Chinese Academy of Sciences (CN), Beijing Jiaotong University (CN), Beijing Normal University (CN), Wuhan University (CN), Beijing University of Technology (CN), Institute of Computing Technology (CN)
National Natural Science Foundation of China
Responsible consumption and production
Openalex Percentile: Top 86%
Distributed and Parallel Computing Systems
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