MVCom: Scheduling Most Valuable Committees for the Large-Scale Sharded Blockchain

Huawei Huang, Zhenyi Huang, Xiaowen Peng, Zibin Zheng, Song Guo
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引用次数: 5

Abstract

In a large-scale sharded blockchain, transactions are processed by a number of parallel committees collaboratively. Thus, the blockchain throughput can be strongly boosted. A problem is that some groups of blockchain nodes consume large latency to form committees at the beginning of each epoch. Furthermore, the heterogeneous processing capabilities of different committees also result in unbalanced consensus latency. Such unbalanced two-phase latency brings a large cumulative age to the transactions waited in the final committee. Consequently, the blockchain throughput can be significantly degraded because of the large transaction's cumulative age. We believe that a good committee-scheduling strategy can reduce the cumulative age, and thus benefit the blockchain throughput. However, we have not yet found a committee-scheduling scheme that works for accelerating block formation in the context of blockchain sharding. To this end, this paper studies a fine-balanced tradeoff between the transaction's throughput and their cumulative age in a large-scale sharded blockchain. We formulate this tradeoff as a utility-maximization problem, which is proved NP-hard. To solve this problem, we propose an online distributed Stochastic-Exploration (SE) algorithm, which guarantees a near-optimal system utility. The theoretical convergence time of the proposed algorithm as well as the performance perturbation brought by the committee's failure are also analyzed rigorously. We then evaluate the proposed algorithm using the dataset of blockchain-sharding transactions. The simulation results demonstrate that the proposed SE algorithm shows an overwhelming better performance comparing with other baselines in terms of both system utility and the contributing degree while processing shard transactions.
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MVCom:为大规模分片区块链调度最有价值的委员会
在大规模分片区块链中,交易由多个并行委员会协同处理。因此,区块链的吞吐量可以大大提高。一个问题是,在每个epoch开始时,一些区块链节点组会消耗大量延迟来组建委员会。此外,不同委员会的异构处理能力也导致了不平衡的共识延迟。这种不平衡的两阶段延迟给最终委员会中等待的事务带来了很大的累积时间。因此,由于大交易的累积时间,区块链吞吐量可能会显著降低。我们认为,一个好的委员会调度策略可以减少累积年龄,从而有利于区块链的吞吐量。然而,我们还没有找到一个委员会调度方案,可以在区块链分片的背景下加速块的形成。为此,本文研究了大规模分片区块链中交易吞吐量与其累积时间之间的精细平衡权衡。我们将这种权衡表述为效用最大化问题,并证明了np困难。为了解决这一问题,我们提出了一种在线分布式随机探索(SE)算法,该算法保证了近乎最优的系统效用。对算法的理论收敛时间以及委员会失效带来的性能扰动进行了严格的分析。然后,我们使用区块链分片交易数据集评估所提出的算法。仿真结果表明,在处理分片事务时,所提出的SE算法在系统效用和贡献程度方面都比其他基准具有压倒性的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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