Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163836
Title: Reliable distributed computing for metaverse: a hierarchical game-theoretic approach
Authors: Jiang, Yuna
Kang, Jiawen
Niyato, Dusit
Ge, Xiaohu
Xiong, Zehui
Miao, Chunyan
Shen, Sherman Xuemin
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Source: Jiang, Y., Kang, J., Niyato, D., Ge, X., Xiong, Z., Miao, C. & Shen, S. X. (2022). Reliable distributed computing for metaverse: a hierarchical game-theoretic approach. IEEE Transactions On Vehicular Technology, 1-16. https://dx.doi.org/10.1109/TVT.2022.3204839
Project: AISG2-RP-2020-019 
RG16/20 
SRG-ISTD-2021-165 
SUTD-ZJU (VP) 202102 
SUTD-ZJU (SD) 202101 
Journal: IEEE Transactions on Vehicular Technology 
Abstract: The metaverse is regarded as a new wave of technological transformation that provides a virtual space for people to interact through digital avatars. To achieve immersive user experiences in the metaverse, real-time rendering is the key technology. However, computing intensive tasks of real-time rendering from metaverse service providers cannot be processed efficiently on a single resource-limited mobile device. Alternatively, such mobile devices can offload the metaverse rendering tasks to other mobile devices by adopting the collaborative computing paradigm based on Coded Distributed Computing (CDC). Therefore, this paper introduces a hierarchical game-theoretic CDC framework for the metaverse services, especially for vehicular metaverse. In the framework, idle resources from vehicles, acting as CDC workers, are aggregated to handle intensive computation tasks in the vehicular metaverse. Specifically, in the upper layer, a miner coalition formation game is formulated based on a reputation metric to select reliable workers. To guarantee the reliable management of reputation values, the reputation values calculated based on the subjective logical model are maintained in a blockchain database. In the lower layer, a Stackelberg game based incentive mechanism is considered to attract reliable workers selected in the upper layer to participate in rendering tasks. The simulation results illustrate that the proposed framework is resistant to malicious workers. Compared with the baseline schemes, the proposed scheme can improve the utility of metaverse service provider and average profit of CDC workers.
URI: https://hdl.handle.net/10356/163836
ISSN: 0018-9545
DOI: 10.1109/TVT.2022.3204839
Schools: School of Computer Science and Engineering 
Rights: © 2022 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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