4.7 Article

From Resource Auction to Service Auction: An Auction Paradigm Shift in Wireless Networks

期刊

IEEE WIRELESS COMMUNICATIONS
卷 29, 期 2, 页码 185-191

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MWC.005.2100627

关键词

Quality of service; Pricing; Wireless networks; Edge computing; Resource management; 5G mobile communication; Routing

资金

  1. U.S. National Science Foundation [CNS-2106589, IIS-1722791]

向作者/读者索取更多资源

This article discusses the concept of end-to-end (E2E) service auction in 5G and beyond, where emerging services like edge computing/intelligence demand heterogeneous CCS resources. By addressing the joint problem of network optimization and auction design, this auction model can provide E2E QoS guarantees while ensuring economic properties.
In 5G and beyond, newly emerging services, such as edge computing/intelligence services, may demand the provisioning of heterogeneous communications, computing, and storage (CCS) resources on and across network entities multiple hops apart. In such cases, traditional resource-oriented auction schemes, where buyers place bids on resources, may not be effective in providing end-to-end (E2E) quality of service (QoS) guarantees. To overcome these limitations, in this article, we discuss the concept of E2E service auction where the auction commodities are E2E services rather than a certain resource. Under this framework, buyers simply bid for services with E2E QoS requirements without having to know the inner working (how to select and valuate resources behind). To guarantee E2E QoS for winning bids while ensuring essential economic properties, E2E service auction requires addressing the joint problem of network optimization and auction design with both economic and QoS constraints. To substantiate the mechanism design, we illustrate how to devise E2E service auctions for edge computing systems under various scenarios. We also identify the research opportunities on E2E service auction mechanism design for other critical use cases, including edge intelligence.

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