Archive for the ‘microverse’ tag
Networked Metaverse Systems
The term ‘Metaverse’ often denotes a wide range of existing and fictional applications. Nevertheless, there are actual systems today that can be studied and analyzed. However, whereas a considerable body of work has been published on applications and application ideas, there is less work on the technical implementation of such systems, especially from a networked systems perspective.
In a recently published open access journal article, we share some insights into the technical design of Metaverse systems, their key technologies, and their shortcomings, predominantly from a networked systems perspective. For the scope of this study, we define the ‘Metaverse’ as follows. The ‘Metaverse’ encompasses various current and emerging technologies, and the term is used to describe different applications, ranging from Augmented Reality (AR), Virtual Reality (VR),and Extended Reality (XR) to a new form of the Internet or Web. A key feature distinguishing the Metaverse from simple AR/VR is its inherently collaborative and shared nature, enabling interaction and collaboration among users in a virtual environment.
Building on Existing Platforms and Network Stacks
Most current Metaverse systems and designs are built on existing technologies and networks. For example, massively multiplayer online games such as Fortnite use a generalized client-server model. In this model, the server authoritatively manages the game state, while the client maintains a local subset of this state and can predict game flow by executing the same game code as the server on approximately the same data. Servers send information about the game world to clients by replicating relevant actors and their properties. Commercial social VR platforms such as Horizon Worlds and AltspaceVR use HTTPS to report client-side information and synchronize in-game clocks across users.
Mozilla Hubs, built with A-Frame (a web framework for building virtual reality experiences), uses WebRTC communication with a Selective Forwarding Unit (SFU). The SFU receives multiple audio and video data streams from its peers, then determines and forwards relevant data streams to connected peers. Blockchain or Non-Fungible Token (NFT)-based online games, such as Decentraland, run exclusively on the client side but allow for various data flow models, ranging from local effects and traditional client-server architectures to peer-to-peer (P2P) interactions based on state channels; Upland is built on EOSIO, an open-source blockchain protocol for scalable decentralized applications, and transports data through HTTPS. Connections between peers in Upland are established using TLS or VPN tunnels.
Many studies have focused on improving various aspects of Metaverse systems. For example, EdgeXAR is a mobile AR framework using edge offloading to enable lightweight tracking with six degrees of freedom (DOF) while reducing offloading delay from the user’s view; SORAS is an optimal resource allocation scheme for edgeenabled Metaverse, using stochastic integer programming to minimize the total network cost; Ibrahim et al. explores the issue of partial computation offloading for multiple subtasks in an in-network computing environment, aiming to minimize energy consumption and delay. However, these ideas for offloading computation and rendering tasks to edge platforms often conflict with the existing end-to-end transport protocols and overlay deployment models. Recently, a Deep Reinforcement Learning (DRL)-based multipath network orchestration framework designed for remote healthcare services is presented, automating subflow management to handle multipath networks. However, proposals for scalable multi-party communication would require interdomain multicast services, unavailable on today’s Internet.
Disconnect Between High-Level Concepts and Actual Systems
In practice, there is a significant disconnect between high-level Metaverse concepts, ideas for technical improvements, and systems that are actually developed and partially deployed. A 2022 ACM IMC paper titled Are we ready for metaverse?: a measurement study of social virtual reality platforms analyzes the performance of various social VR systems, pinpointing numerous issues related to performance, communication overhead, and scalability. These issues are primarily due to the fact that current systems leverage existing platforms, protocols, and system architectures, which cannot tap into any of the proposed architectural and technical enhancements, such as scalable multi-party communication, offloading computation, rendering tasks, etc.
Rather than merely layering ‘the Metaverse’ on top of legacy and not always ideal foundations, we consider Metaverse as a driver for future network and web applications and actively develop new designs to that end. In our article, we take a comprehensive systems approach and technically describe current Metaverse systems, focusing on their networking aspects. We document the requirements and challenges of Metaverse systems and propose a principled approach to system design for these requirements and challenges based on a thorough understanding of the needs of Metaverse systems, the current constraints and limitations, and the potential solutions of Internet technologies.
Article Overview
- We present a technical description of the ‘Metaverse’ based on existing and emerging systems, including a discussion of its fundamental properties, applications, and architectural models.
- We comprehensively study relevant enabling technologies for Metaverse systems, including HCI/XR technologies, networking, communications, media encoding, simulation, real-time rendering and AI. We also discuss current Metaverse system architectures and the integration of these technologies into actual applications.
- We conduct a detailed requirements analysis for constructing Metaverse systems. We analyze applications specific requirements and identify existing gaps in four key aspects: communication performance, mobility, large-scale operation,and end system architecture. For each area, we propose candidate technologies to address these gaps.
- We propose a research agenda for future Metaverse systems, based on our gap analysis and candidate technologies discussion. We re-assess the fundamental goals and requirements, without necessarily being constrained by existing system architectures and protocols. Based on a comprehensive understanding of what Metaverse systems need and what end-systems, devices, networks and communication services can theoretically provide, we propose specific design ideas and future research directions to realize Metaverse systems that can meet the expectations often articulated in the literature.
References
- Y. Zhang, D. Kutscher and Y. Cui; Networked Metaverse Systems: Foundations, Gaps, Research Directions; in IEEE Open Journal of the Communications Society, doi: 10.1109/OJCOMS.2024.3426098.
- Tianyuan Yu, Xinyu Ma, Varun Patil, Yekta Kocaogullar, Yulong Zhang, Jeff Burke, Dirk Kutscher, Lixia Zhang; Secure Web Objects: Building Blocks for Metaverse Interoperability and Decentralization; IEEE MetaCom 2024; August 12-14 2024; Hong Kong, China
- Dirk Kutscher, Jeff Burke, Giuseppe Fioccola, Paulo Mendes;
Statement: The Metaverse as an Information-Centric Network; 10th ACM Conference on Information-Centric Networking (ACM ICN '23); October 9 — 10, 2023, Reykjavik, Iceland - Giuseppe Fioccola , Paulo Mendes , Jeff Burke , Dirk Kutscher;
Information-Centric Metaverse; Internet Draft draft-fmbk-icnrg-metaverse-01; Work in Progress; July 2023