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

被引:1
作者
Shaikh, Shahzaib [1 ]
Jammal, Manar [1 ]
机构
[1] York Univ, Sch Informat Technol, Toronto, ON, Canada
关键词
Metaverse; Edge computing; Fault tolerance; Failure remediation; Distributed systems; Machine learning; PLACEMENT;
D O I
10.1016/j.comnet.2024.110803
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:11
相关论文
共 70 条
[11]   CRACAU: Byzantine Machine Learning Meets Industrial Edge Computing in Industry 5.0 [J].
Du, Anran ;
Shen, Yicheng ;
Zhang, Qinzi ;
Tseng, Lewis ;
Aloqaily, Moayad .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 18 (08) :5435-5445
[12]   A Reliability-aware Computation Offloading Solution via UAV-mounted Cloudlets [J].
El Haber, Elie ;
Alameddine, Hyame Assem ;
Assi, Chadi ;
Sharafeddine, Sanaa .
PROCEEDING OF THE 2019 IEEE 8TH INTERNATIONAL CONFERENCE ON CLOUD NETWORKING (CLOUDNET), 2019,
[13]   Dynamic Reliability Management of Multigateway IoT Edge Computing Systems [J].
Ergun, Kazim ;
Ayoub, Raid ;
Mercati, Pietro ;
Rosing, Tajana Simunic .
IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (05) :3864-3889
[14]   FIBFT: An Improved Byzantine Consensus Mechanism for Edge Computing [J].
Gao, Ningjie ;
Huo, Ru ;
Wang, Shuo ;
Huang, Tao .
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC, 2023,
[15]   Automata-Based Dynamic Fault Tolerant Task Scheduling Approach in Fog Computing [J].
Ghanavati, Sara ;
Abawajy, Jemal ;
Izadi, Davood .
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING, 2022, 10 (01) :488-499
[16]  
Hou XW, 2020, IEEE CONF COMPUT, P150, DOI [10.1109/INFOCOMWKSHPS50562.2020.9163048, 10.1109/infocomwkshps50562.2020.9163048]
[17]  
Hu JY, 2020, PROCEEDINGS OF THE 17TH USENIX SYMPOSIUM ON NETWORKED SYSTEMS DESIGN AND IMPLEMENTATION, P619
[18]   Proactive Failure Recovery for NFV in Distributed Edge Computing [J].
Huang, Huawei ;
Guo, Song .
IEEE COMMUNICATIONS MAGAZINE, 2019, 57 (05) :131-137
[19]   Fault Tolerance of Stateful Microservices for Industrial Edge Scenarios [J].
Jia, Yuke ;
Wang, Tiejun ;
Qiu, Tianbo ;
Zhang, Xiaohan ;
Wang, Rui ;
Wo, Tianyu .
2023 IEEE INTERNATIONAL CONFERENCE ON JOINT CLOUD COMPUTING, JCC, 2023, :50-56
[20]   Efficient Fault-Tolerant Consensus for Collaborative Services in Edge Computing [J].
Jing, Guanlin ;
Zou, Yifei ;
Yu, Dongxiao ;
Luo, Chuanwen ;
Cheng, Xiuzhen .
IEEE TRANSACTIONS ON COMPUTERS, 2023, 72 (08) :2139-2150