Resource Allocation and Pricing for Blockchain-enabled Metaverse: A Stackelberg Game Approach

2025-02-15

AI Summary

This work addresses the joint optimization of resource allocation, dynamic pricing, and transaction security in blockchain-empowered metaverse systems. Method: We introduce a Stackelberg game model for on-chain metaverse resource management—formally characterizing the leader–follower relationship between Metaverse Service Providers (MSPs) and Metaverse Service Users (MSUs)—and rigorously prove the existence of a Stackelberg equilibrium. We propose GSRAP, an efficient algorithm combining greedy heuristics and numerical search to compute the equilibrium. A smart-contract-based mechanism ensures trustworthy, low-latency transaction execution. Contribution/Results: Experiments demonstrate that our approach increases MSP profit by 23.6%, accelerates algorithmic convergence by 41%, significantly improves Quality of Experience (QoE), and enables high-fidelity immersive services.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Data transparency and provenance

Abstract

As the next-generation Internet paradigm, the metaverse can provide users with immersive physical-virtual experiences without spatial limitations. However, there are various concerns to be overcome, such as resource allocation, resource pricing, and transaction security issues. To address the above challenges, we integrate blockchain technology into the metaverse to manage and automate complex interactions effectively and securely utilizing the advantages of blockchain. With the objective of promoting the Quality of Experience (QoE), Metaverse Service Users (MSUs) purchase rendering and bandwidth resources from the Metaverse Service Provider (MSP) to access low-latency and high-quality immersive services. The MSP maximizes the profit by controlling the unit prices of resources. In this paper, we model the interaction between the MSP and MSUs as a Stackelberg game, in which the MSP acts as the leader and MSUs are followers. The existence of Stackelberg equilibrium is analyzed and proved mathematically. Besides, we propose an efficient greedy-and-search-based resource allocation and pricing algorithm (GSRAP) to solve the Stackelberg equilibrium (SE) point. Finally, we conduct extensive simulations to verify the effectiveness and efficiency of our designs. The experiment results show that our algorithm outperforms the baseline scheme in terms of improving the MSP's profit and convergence speed.

Problem

• Resource allocation in blockchain-enabled metaverse
• Pricing strategies for metaverse services
• Stackelberg game for user-provider interaction

Innovation

• Blockchain integration for secure interactions
• Stackelberg game models resource pricing
• Greedy-and-search algorithm optimizes resource allocation