MuMeNet: A Network Simulator for Musical Metaverse Communications

2025-12-04

AI Summary

Music Metaverse (MM) systems face significant challenges in supporting their high interactivity, strong heterogeneity, and multicast-oriented traffic characteristics due to limitations in existing network and service infrastructures. To address this, we first formally model MM session service requirements and propose a unified network-service joint graph model tailored for 5G/6G environments. We then design MuMeNet—a lightweight discrete-event simulator specifically engineered for dynamic MM traffic—capable of emulating multi-user, ultra-low-latency, multicast scenarios such as virtual concerts and enabling end-to-end service orchestration. Integrating linear programming–based optimization, MuMeNet facilitates fine-grained performance evaluation of service deployment under realistic workloads. Experimental results demonstrate that MuMeNet effectively guarantees quality-of-service (QoS) under sub-10-ms end-to-end latency and high concurrency, establishing a reproducible benchmark for evaluating MM-specific network architectures and protocol designs.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Multiagent Systems: Mechanism Design
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Web Mining and Content Analysis: Web data generation and simulation
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

The Metaverse, a shared and spatially organized digital continuum, is transforming various industries, with music emerging as a leading use case. Live concerts, collaborative composition, and interactive experiences are driving the Musical Metaverse (MM), but the requirements of the underlying network and service infrastructures hinder its growth. These challenges underscore the need for a novel modeling and simulation paradigm tailored to the unique characteristics of MM sessions, along with specialized service provisioning strategies capable of capturing their interactive, heterogeneous, and multicast-oriented nature. To this end, we make a first attempt to formally model and analyze the problem of service provisioning for MM sessions in 5G/6G networks. We first formalize service and network graph models for the MM, using "live audience interaction in a virtual concert" as a reference scenario. We then present MuMeNet, a novel discrete-event network simulator specifically tailored to the requirements and the traffic dynamics of the MM. We showcase the effectiveness of MuMeNet by running a linear programming based orchestration policy on the reference scenario and providing performance analysis under realistic MM workloads.

Problem

• Develops a network simulator for Musical Metaverse communications
• Models service provisioning in 5G/6G networks for interactive sessions
• Addresses network challenges of live, heterogeneous, multicast music experiences

Innovation

• Network simulator tailored for Musical Metaverse
• Formal service and network graph models for 5G/6G
• Linear programming orchestration policy for performance analysis