Survey of fault management techniques for edge-enabled distributed metaverse applications

Abstract

The metaverse, envisioned as a vast, distributed virtual world, relies on edge computing for low-latency data processing. However, ensuring fault tolerance – the system’s ability to handle failures – is critical for a seamless user experience. This paper analyzes existing research on fault tolerance in edge computing over the past six years, specifically focusing on its applicability to the metaverse. We identify common fault types like node failures, communication disruptions, and security issues. The analysis then explores various fault management techniques including proactive monitoring, resource optimization, task scheduling, workload migration, redundancy for service continuity, machine learning for predictive maintenance, and consensus algorithms to guarantee data integrity. While these techniques hold promise, adaptations are necessary to address the metaverse’s real-time interaction requirements and low-latency constraints. This paper analyzes existing research and identifies key areas for improvement, providing valuable research guidelines and insights to pave the way for the development of fault management techniques specifically tailored to the metaverse, ultimately contributing to a robust and secure virtual world.