Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse

被引:1
|
作者
Lin, Yijing [1 ]
Gao, Zhipeng [1 ]
Du, Hongyang [2 ]
Niyato, Dusit [2 ]
Kang, Jiawen [3 ]
Xiong, Zehui [4 ]
Zheng, Zibin [5 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
[2] Nanyang Technol Univ, Coll Comp & Data Sci, Singapore 639798, Singapore
[3] Guangdong Univ Technol, Guangzhou 510006, Peoples R China
[4] Singapore Univ Technol & Design, Singapore 487372, Singapore
[5] Sun Yat Sen Univ, Sch Software Engn, Zhuhai 519082, Guangdong, Peoples R China
基金
中国国家自然科学基金; 新加坡国家研究基金会;
关键词
Semantics; Metaverse; Data mining; Blockchains; Resource management; Measurement; Computational modeling; AI-Generated content; blockchain; semantic communication; SEMANTIC COMMUNICATION-SYSTEMS; JOINT OPTIMIZATION; INTERNET; MARKET;
D O I
10.1109/TSC.2024.3382958
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms.
引用
收藏
页码:2067 / 2079
页数:13
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