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A Tutorial on Meta-Services and Services Computing in Metaverse
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AI
DOI：10.1109/JIOT.2023.3346901.png)
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摘要
En 中文
The metaverse, as a paradigm continuously evolving in the next generation of the Internet, aims to integrate various network applications. However, existing applications on the Internet, such as serve computing, and edge computing, have highly complex technical requirements. These applications face compatibility issues with the metaverse in terms of protocols, applications, and services. So they cannot be directly integrated into the metaverse. How to efficiently deploy service computing in the metaverse has become a hotspot research area. Moreover, metaverse implements innovative services to offer individuals more immersive experiences, such as acrlong VR services and augmented Reality services. These new services demand high-computational resources, including computing power, network performance, data security, etc. Ensuring optimal service quality for these new services in the metaverse is another critical aspect of metaverse research. To address the aforementioned challenges, Meta-services, designed to describe, discover, compose, and manage other services, are gradually attracting widespread attention and research. In this article, we provide a comprehensive review, analysis, and discussion of existing research work. We summarize the services computing and novel services in metaverse and categorize the meta-services framework into three layers: 1) meta-bottom layer (meta-data); 2) meta-middle layer (meta-models, meta-objects, and meta-languages); and 3) meta-top layer (meta-programming). Based on the meta-services framework, we discuss some current challenges, as well as provide future research directions. We hope that this article can enable readers to quickly understand the reasons for each problem and the current research progress, thereby providing guidance and motivation for further research in this field.
Keyword:
Codes
Meta-services framework
metaverse
services computing
期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
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