# Compute- and Data-Intensive Networks: The Key to the Metaverse

arXiv: https://arxiv.org/abs/2204.02001 · HTML: https://mlsanity.com/paper/2204.02001/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Apr 2022.

## Built on by (most cited first, 9 of 9)

- [Edge Computing for Semantic Communication Enabled Metaverse: An Incentive Mechanism Design](https://mlsanity.com/paper/2212.06463/) (2022)
- [The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions](https://mlsanity.com/paper/2304.09240/) (2023)
- [Human-Centric Resource Allocation for the Metaverse With Multiaccess Edge Computing](https://mlsanity.com/paper/2312.15313/) (2023)
- [Dynamic Partial Computation Offloading for the Metaverse in In-Network Computing](https://mlsanity.com/paper/2306.06022/) (2023)
- [Need of 6G for the Metaverse Realization](https://mlsanity.com/paper/2301.03386/) (2022)
- [Metaverse Survey & Tutorial: Exploring Key Requirements, Technologies, Standards, Applications, Challenges, and Perspectives](https://mlsanity.com/paper/2405.04718/) (2024)
- [A Flexible Multi-Agent Deep Reinforcement Learning Framework for Dynamic Routing and Scheduling of Latency-Critical Services](https://mlsanity.com/paper/2510.11535/) (2025)
- [A Constrained RL Approach for Cost-Efficient Delivery of Latency-Sensitive Applications](https://mlsanity.com/paper/2603.04353/) (2026)
- [From Prior-Guided Heuristics to Deployable Agents: Accelerating Demonstration-Driven Reinforcement Learning for Deadline-Constrained Network Control](https://mlsanity.com/paper/2609.03590/) (2026)

## Abstract (arXiv)

The worlds of computing, communication, and storage have for a long time been treated separately, and even the recent trends of cloud computing, distributed computing, and mobile edge computing have not fundamentally changed the role of networks, still designed to move data between end users and pre-determined computation nodes, without true optimization of the end-to-end compute-communication process. However, the emergence of Metaverse applications, where users consume multimedia experiences that result from the real-time combination of distributed live sources and stored digital assets, has changed the requirements for, and possibilities of, systems that provide distributed caching, computation, and communication. We argue that the real-time interactive nature and high demands on data storage, streaming rates, and processing power of Metaverse applications will accelerate the merging of the cloud into the network, leading to highly-distributed tightly-integrated compute- and data-intensive networks becoming universal compute platforms for next-generation digital experiences. In this paper, we first describe the requirements of Metaverse applications and associated supporting infrastructure, including relevant use cases. We then outline a comprehensive cloud network flow mathematical framework, designed for the end-to-end optimization and control of such systems, and show numerical results illustrating its promising role for the efficient operation of Metaverse-ready networks.