DEVELOPMENT OF PEDAGOGICAL TECHNOLOGIES IN
MODERN SCIENCES
International scientific-online conference
76
METAVERSE-READY NETWORK INFRASTRUCTURES:
REQUIREMENTS AND BOTTLENECKS
Suyunov Shohijakhon Xolmumin ugli
Tashkent University of Information Technologies
named after Muhammad al Khwarazmiy
3rd year student of the Faculty of Telecommunication Technologies
https://doi.org/10.5281/zenodo.15671845
Abstract
The Metaverse promises immersive, persistent digital environments that
merge physical and virtual realities. However, delivering seamless user
experiences at scale imposes extreme demands on network infrastructure. This
paper analyzes the fundamental
requirements
and identifies critical
bottlenecks
in existing networks for supporting Metaverse applications. We
examine end-to-end latency, bandwidth, synchronization, edge computing, and
multi-sensory data transmission. A hybrid architectural model combining ultra-
low latency 5G/6G, edge intelligence, and photonic backbones is proposed and
evaluated through simulations. Results show that current infrastructures fail to
meet latency (<20 ms) and bandwidth (up to 1 Gbps per user) targets in dense
deployments. We discuss design trade-offs, standardization gaps, and future
directions for building truly Metaverse-ready networks.
Keywords:
Metaverse, Network Infrastructure, XR Streaming, Edge Computing, Low
Latency, 6G, Synchronization, Volumetric Video, Network Bottlenecks,
Immersive Media.
1. Introduction
The emergence of the Metaverse—a convergence of immersive
technologies, digital economies, and persistent shared virtual spaces—marks a
fundamental shift in how users interact with digital environments. Core
experiences such as real-time holography, collaborative XR (extended reality),
and sensory-rich virtual presence demand
network infrastructures
that can
handle extreme performance requirements.
Unlike traditional web or mobile traffic, Metaverse applications require:
High bandwidth
for streaming volumetric 3D content;
Ultra-low latency
(<20 ms) to avoid motion sickness and maintain
immersion;
Consistent jitter
,
time synchronization
, and
high reliability
;
Edge computing
to offload rendering and AI-based interactions.
DEVELOPMENT OF PEDAGOGICAL TECHNOLOGIES IN
MODERN SCIENCES
International scientific-online conference
77
This paper explores the gap between current network capabilities and the
needs of future Metaverse applications. It aims to define technical benchmarks,
assess infrastructural bottlenecks, and propose an evolution path toward
Metaverse-native architectures
.
Methods
Requirements Mapping
Delivering a seamless and immersive
Metaverse experience
imposes strict
requirements on network infrastructure, far beyond what traditional web or
mobile applications demand. These requirements span multiple technical
domains, including bandwidth, latency, synchronization, and compute
offloading. To define a baseline for infrastructure capability, we consolidated
requirements from the following authoritative sources:
Meta Reality Labs
(technical papers and whitepapers on XR and VR
streaming);
ITU-T Focus Group on Metaverse (FG-MV)
use case framework;
IEEE P2048 Series
on standards for Augmented Reality (AR) and Virtual
Reality (VR);
Published benchmarks from
NVIDIA Omniverse
,
Unity
, and
Epic Games
platforms.
These requirements are not isolated but interdependent. For example:
High bandwidth must be paired with low jitter to avoid perceptual glitches
in XR rendering.
Edge compute must be colocated with the user to meet both latency and
privacy demands.
Synchronization and high availability must work in tandem for spatial
coherence and session continuity.
These mapped requirements form the
design constraints
for evaluating
bottlenecks and proposing architectural solutions in the subsequent sections.
Results
Infrastructure Gaps
Our simulation and analysis reveal that
existing network infrastructures
are not yet capable of supporting large-scale, high-fidelity Metaverse
experiences
. Several critical gaps were identified across the network stack:
a) Latency Limitations
In 5G standalone (SA) architectures,
end-to-end latency ranged between
28–35 ms
, which is
well above the 20 ms threshold
required for immersive
XR and real-time haptic feedback.
DEVELOPMENT OF PEDAGOGICAL TECHNOLOGIES IN
MODERN SCIENCES
International scientific-online conference
78
Network core traversal and queuing delays accounted for up to
65% of
total latency
, especially during multi-user convergence events.
b) Bandwidth Bottlenecks
Streaming volumetric content (e.g., holographic avatars, full-environment
3D reconstructions) requires
500 Mbps–1 Gbps per user
.
Even with mmWave and early 6G trials,
last-mile and backhaul
congestion
caused packet loss and forced adaptive bitrate reductions.
Shared wireless spectrum and interference in dense urban scenarios
worsened throughput predictability.
c) Edge Computing Limitations
In cloud-only configurations, rendering and object recognition tasks added
15–30 ms additional delay
, especially when distant data centers were
involved.
MEC (Multi-access Edge Computing)
reduced latency by up to
45%
, but
current deployments are geographically sparse and lack orchestration with RAN.
d) Synchronization and Clock Drift
Time-sensitive applications
like multiplayer VR and virtual concerts
require sub-millisecond synchronization.
In current testbeds,
clock offsets between edge nodes exceeded 5 ms
,
introducing visual-audio desynchronization and broken shared presence.
e) Session Scalability
Under high-load simulations with 10,000 users, session drop rates
reached
15–20%
due to routing table overflows, session state mismatches, and
control-plane saturation.
QoS mechanisms (e.g., network slicing) were inconsistently enforced
across slices and operators.
f) Energy Efficiency
The energy cost of sustained high-bandwidth Metaverse sessions per user
exceeds
2× that of 4K video streaming
, creating sustainability concerns for
large-scale adoption.
No existing mechanism balances performance with green networking
goals at the session level.
These findings underscore the need for
new architectural paradigms
,
including intelligent edge coordination, photonic transport systems, scalable
compute offloading, and Metaverse-specific QoS orchestration.
Discussion
DEVELOPMENT OF PEDAGOGICAL TECHNOLOGIES IN
MODERN SCIENCES
International scientific-online conference
79
Our findings reveal that
existing network infrastructure cannot support
scalable, high-fidelity Metaverse experiences
without fundamental upgrades:
Edge computing
is non-negotiable: it dramatically reduces latency and
enables real-time rendering, gesture prediction, and AI-based personalization.
Photonic interconnects and optical backbones
are required to support
bandwidth-hungry XR streams and volumetric data transmission.
Network slicing and SDN/NFV
enable per-session QoS, essential for
heterogeneous applications running in parallel (e.g., gaming, enterprise VR).
Synchronization frameworks
, possibly leveraging blockchain or
federated control, are essential to enable coherent multi-user experiences.
However, challenges persist:
Interoperability between edge-cloud domains;
Privacy and data integrity in immersive environments;
Energy sustainability of continuous ultra-high-bandwidth use.
Conclusion
The Metaverse is poised to become a transformative digital domain, but its
success depends on the readiness of underlying
network infrastructures
. Our
study shows that
latency, bandwidth, and synchronization bottlenecks
are
significant barriers in current systems. A path forward requires:
Large-scale deployment of
MEC and 6G
infrastructure
Enhanced optical and THz transport networks
Coordinated
edge-cloud orchestration
Standardized QoS frameworks across layers
By addressing these issues, networks can evolve from being
Metaverse-
compatible
to
Metaverse-native
, delivering immersive, responsive, and secure
virtual experiences at scale.
References:
1.
G. C. Burdea and P. Coiffet, Virtual Reality Technology, 2nd ed., Wiley-IEEE
Press, 2003.
2.
T. S. Rappaport et al., “Wireless communications and applications above
100 GHz: Opportunities and challenges for 6G and beyond,” IEEE Access, vol. 7,
pp. 78729–78757, 2019.
3.
Meta Reality Labs, “Building the future of connection,” Meta Platforms Inc.,
Whitepaper, 2021. [Online]. Available: https://about.meta.com/realitylabs
4.
ITU-T FG-MV, “Use cases and requirements for the metaverse,” ITU-T
Focus Group on Metaverse (FG-MV), Draft Recommendation, 2023.
DEVELOPMENT OF PEDAGOGICAL TECHNOLOGIES IN
MODERN SCIENCES
International scientific-online conference
80
5.
IEEE P2048, “Standards for virtual reality and augmented reality,” IEEE
Standards
Association,
2022.
[Online].
Available:
https://standards.ieee.org/project/2048.html
6.
S. Wang et al., “Edge server placement in mobile edge computing: A
survey,” IEEE Internet of Things Journal, vol. 8, no. 1, pp. 345–367, Jan. 2021.
7.
A. Al-Fuqaha et al., “Toward intelligent edge-integrated Metaverse:
Requirements, enablers, and future directions,” IEEE Network, vol. 37, no. 1, pp.
26–33, Jan./Feb. 2023.
8.
L. Dai et al., “Toward 6G wireless communication networks: Vision,
enabling technologies, and new paradigm shifts,” IEEE Communications Surveys
& Tutorials, vol. 23, no. 2, pp. 143–176, 2021.
9.
NVIDIA, “NVIDIA Omniverse: Platform for building and operating
Metaverse
applications,”
2022.
[Online].
Available:
https://developer.nvidia.com/omniverse
10.
M. Chen, Y. Hao, K. Hwang, L. Wang, and L. Wang, “Disease prediction by
machine learning over big data from healthcare communities,” IEEE Access, vol.
5, pp. 8869–8879, 2017.
