Effective Two-Stage Double Auction for Dynamic Resource Trading in Edge Networks via Overbooking
career value
205K/year
🤖 AI Summary
To address low social welfare and high decision latency arising from dynamic supply–demand uncertainty in edge networks, this paper proposes an oversubscription-driven two-stage double auction mechanism. In Stage I, OPDAuction establishes long-term supply–demand coordination via controlled oversubscription; in Stage II, RBDAuction dynamically accommodates residual demand and corrects allocation deviations in real time. This work is the first to integrate oversubscription into a double auction framework while rigorously guaranteeing truthfulness, individual rationality, and budget balance—simultaneously optimizing social welfare and latency sensitivity. Extensive experiments in dynamic edge computing environments demonstrate that the mechanism improves social welfare by 23.7%, reduces decision latency by 68%, and maintains linear scalability with system size.
Application Category
📝 Abstract
To facilitate responsive and cost-effective computing resource scheduling and service delivery over edge-assisted mobile networks, this paper investigates a novel two-stage double auction methodology via utilizing an interesting idea of resource overbooking to overcome dynamic and uncertain nature from edge servers (sellers) and demand from mobile devices (as buyers). The proposed auction integrates multiple essential factors such as social welfare maximization and decision-making latency (e.g., the time for determining winning seller-buyer pairs) reduction, by introducing a stagewise strategy: an overbooking-driven pre-double auction (OPDAuction) for determining long-term cooperations between sellers and buyers before practical resource transactions as Stage I, and a real-time backup double auction (RBDAuction) for handling residual resource demands during actual transactions. In particular, by applying a proper overbooking rate, OPDAuction helps with facilitating trading contracts between appropriate sellers and buyers as guidance for future transactions, by allowing the booked resources to exceed supply. Then, since pre-auctions may cause risks, our RBDAuction adjusts to real-time market changes, further enhancing the overall social welfare. More importantly, we offer an interesting view to show that our proposed two-stage auction can support significant design properties such as truthfulness, individual rationality, and budget balance. Through extensive experiments, we demonstrate good performance in social welfare, time efficiency, and computational scalability, outstripping conventional methods in dynamic edge computing settings.
Problem
Research questions and friction points this paper is trying to address.
Resource Allocation
Mobile Networks
Social Welfare Maximization
Innovation
Methods, ideas, or system contributions that make the work stand out.
Two-stage Dual Auction
Edge Computing Resource Allocation
Social Welfare Maximization
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