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

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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.
Funding Information
  • Academic Divisions of the Chinese Academy of Sciences (2020-ZW12-A-024)
  • National Natural Science Foundation of China (61772044, 62293555, 62402047)
  • Major Program of Science and Technology Innovation 2030 of China (2022ZD0117105)
  • Fundamental Research Funds for the Central Universities (2233100006)
  • Major Program of Natural Science Research Foundation of Anhui Provincial Education Department (2022AH040148)

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