MetaShard：面向元宇宙应用的新型分片区块链平台
MetaShard: A Novel Sharding Blockchain Platform for Metaverse Applications
AI总结：
针对元宇宙区块链面临的资源需求大、可扩展性不足及安全问题，研究提出新型分片区块链框架MetaShard，含参与度证明共识机制与创新分片管理方案，通过混合优化方法在多项式时间内求解，显著提升吞吐量并保障安全。
摘要：
凭借其在虚拟资产验证方面的安全性、透明性与灵活性，区块链已被认定为元宇宙的核心技术之一。遗憾的是，基于区块链的元宇宙面临着资源需求巨大、可扩展性不足及安全隐患等严峻挑战。为解决这些问题，本文提出一种面向元宇宙应用的新型分片区块链框架，名为MetaShard。具体而言，我们首先设计了一种高效的共识机制——参与度证明（Proof-of-Engagement），该机制可激励元宇宙用户（MUs）贡献数据与计算资源。此外，为提升MetaShard的可扩展性，我们提出了一种创新的分片管理方案，在保护分片免受51%攻击的同时最大化网络吞吐量。由于该优化问题是NP完全问题，我们提出了一种混合方法，采用二分搜索法将问题分解为可通过拉格朗日方法有效求解的子问题。由此，所提方法可在多项式时间内得到解，从而实现灵活的分片重配置，并降低敌手腐化风险。大量数值实验表明，与最先进的商业求解器相比，我们的方法在不到1/30的运行时间内，吞吐量最高可提升66.6%。此外，所提方法在大多数实验中均可得到全局最优解。
英文摘要：
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 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
