CIVIC: Cooperative Immersion Via Intelligent Credit-sharing in DRL-Powered Metaverse

TL;DR

CIVIC is a novel DRL-based framework that optimizes resource sharing among Metaverse providers, significantly improving user immersion, request fulfillment, and fairness in complex, dynamic environments.

Contribution

Introduces CIVIC, a cooperative resource sharing framework integrating DRL, credit sharing, and immersion-aware provisioning for Metaverse service providers.

Findings

CIVIC achieves 12-36% higher request completion rates.

CIVIC improves fulfillment rates by 23-70%.

CIVIC enhances fairness and robustness under dynamic loads.

Abstract

The Metaverse faces complex resource allocation challenges due to diverse Virtual Environments (VEs), Digital Twins (DTs), dynamic user demands, and strict immersion needs. This paper introduces CIVIC (Cooperative Immersion Via Intelligent Credit-sharing), a novel framework optimizing resource sharing among multiple Metaverse Service Providers (MSPs) to enhance user immersion. Unlike existing methods, CIVIC integrates VE rendering, DT synchronization, credit sharing, and immersion-aware provisioning within a cooperative multi-MSP model. The resource allocation problem is formulated as two NP-hard challenges: a non-cooperative setting where MSPs operate independently and a cooperative setting utilizing a General Credit Pool (GCP) for dynamic resource sharing. Using Deep Reinforcement Learning (DRL) for tuning resources and managing cooperating MSPs, CIVIC achieves 12-36% higher request completion, 23-70% higher fulfillment rates, 20-60% more served clients, and up to 51% more fairly distributed requests, all with competitive costs. Extensive experiments demonstrate CIVIC's resilience, adaptability, and robust performance under dynamic load conditions and unexpected demand surges, making it suitable for real-world distributed Metaverse infrastructures.