Towards Context-Aware Edge-Cloud Continuum Orchestration for Multi-user XR Services

TL;DR

This paper proposes a layered, context-aware mathematical model for orchestrating multi-user XR services across edge and cloud resources, addressing latency and resource management challenges in immersive shared environments.

Contribution

It introduces a novel layered model and formal framework for optimizing edge-cloud orchestration tailored for multi-user XR applications.

Findings

Model effectively captures XR service parameters across layers

Framework demonstrates improved resource allocation strategies

Validation shows feasibility for real-world deployment

Abstract

The rapid growth of multi-user eXtended Reality (XR) applications, spanning fields such as entertainment, education, and telemedicine, demands seamless, immersive experiences for users interacting within shared, distributed environments. Delivering such latency-sensitive experiences involves considerable challenges in orchestrating network, computing, and service resources, where existing limitations highlight the need for a structured approach to analyse and optimise these complex systems. This challenge is amplified by the need for high-performance, low-latency connectivity, where 5G and 6G networks provide essential infrastructure to meet the requirements of XR services at scale. This article addresses these challenges by developing a model that parametrises multi-user XR services across four critical layers of the standard virtualisation architecture. We formalise this model mathematically, proposing a context-aware framework that defines key parameters at each level and integrates them into a comprehensive Edge-Cloud Continuum orchestration strategy. Our contributions include a detailed analysis of the current limitations and needs in existing Edge-Cloud Continuum orchestration approaches, the formulation of a layered mathematical model, and a validation framework that demonstrates the utility and feasibility of the proposed solution.