Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/171803
Title: MetaShard: a novel sharding blockchain platform for metaverse applications
Authors: Nguyen, Cong T.
Hoang, Dinh Thai
Nguyen, Diep N.
Xiao, Yong
Niyato, Dusit
Dutkiewicz, Eryk
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2023
Source: Nguyen, C. T., Hoang, D. T., Nguyen, D. N., Xiao, Y., Niyato, D. & Dutkiewicz, E. (2023). MetaShard: a novel sharding blockchain platform for metaverse applications. IEEE Transactions On Mobile Computing. https://dx.doi.org/10.1109/TMC.2023.3290955
Journal: IEEE Transactions on Mobile Computing
Abstract: Due to its security, transparency, and flexibility in verifying virtual assets, blockchain has been identified as one of the key technologies for Metaverse. Unfortunately, blockchain-based Metaverse faces serious challenges such as massive resource demands, scalability, and security/privacy concerns. To address these issues, this paper proposes a novel sharding-based blockchain framework, namely MetaShard, for Metaverse applications. Particularly, we first develop an effective consensus mechanism, namely Proof-of-Engagement, that can incentivize MUs' data and computing resource contribution. Moreover, to improve the scalability of MetaShard, we propose an innovative sharding management scheme to maximize the network's throughput while protecting the shards from 51% attacks. Since the optimization problem is NP-complete, we develop a hybrid approach that decomposes the problem (using the binary search method) into sub-problems that can be solved effectively by the Lagrangian method. As a result, the proposed approach can obtain solutions in polynomial time, thereby enabling flexible shard reconfiguration and reducing the risk of corruption from the adversary. Extensive numerical experiments show that, compared to the state-of-the-art commercial solvers, our proposed approach can achieve up to 66.6% higher throughput in less than 1/30 running time. Moreover, the proposed approach can achieve global optimal solutions in most experiments.
URI: https://hdl.handle.net/10356/171803
ISSN: 1536-1233
DOI: 10.1109/TMC.2023.3290955
Schools: School of Computer Science and Engineering 
Rights: © 2023 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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