Joint wireless and computing resource management with optimal slice selection in in-network-edge metaverse system

TL;DR

This paper introduces an optimal resource management framework for in-network-edge metaverse systems that jointly allocates wireless and computing resources across slices, enhancing performance under high demand.

Contribution

It formulates a mixed-integer nonlinear programming model for joint resource management and derives an optimal solution, addressing inter-slice and intra-slice allocation challenges.

Findings

Significant performance improvements over benchmarks

Effective balancing of radio and computing resources

Robust under high user demand scenarios

Abstract

This paper presents an approach to joint wireless and computing resource management in slice-enabled metaverse networks, addressing the challenges of inter-slice and intra-slice resource allocation in the presence of in-network computing. We formulate the problem as a mixed-integer nonlinear programming (MINLP) problem and derive an optimal solution using standard optimization techniques. Through extensive simulations, we demonstrate that our proposed method significantly improves system performance by effectively balancing the allocation of radio and computing resources across multiple slices. Our approach outperforms existing benchmarks, particularly in scenarios with high user demand and varying computational tasks.