区块链功能中的基本指标

Anupam Tiwari, Usha Batra
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引用次数: 0

摘要

除了众所周知的金融领域之外,区块链技术在全球范围内的部署和实施已经取得了进展。这些部署在设计上是多样化的,具有不同的体系结构,并且具有不同的功能。通过众所周知的比特币区块链架构的各种技术变体来获得区块链技术的好处存在共性。尽管区块链技术仍处于发展阶段,但它已经能够在行业、公司和治理机制中留下绝对的印记,证实它是确定未来的一部分。到2025年,物联网生态系统的设备估计将达到500亿,区块链技术很快将成为未来智能世界不可或缺的一部分。任何区块链架构的部署都可能能够按照设计完成功能需求,但所需区块链性能的测量仍然依赖于许多参数,这些参数需要平衡和微调。当前,比特币生态系统中出现了交易提交延迟的现象。本文确定了参数对比特币区块链的影响,并通过比特币模拟器测量性能,通过调整区块大小、区块和节点数量等参数来分析性能。对区块链性能的调整效果进行了量化、分析和讨论,重点是在比特币环境中测量和减少交易传播延迟。最后在Jupyter笔记本上绘制了热图模型,并导出了数据集。
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Cardinal Metrics in Blockchain Functioning
Blockchain technology has been acquiring pace in deployments and implementations across globe vide association with large number of domains apart from widely known finance domain. These deployments are variegated in designs, have various architectures and possess functional differences. The commonality exists in deriving the benefits of blockchain technology through various technical variants of the widely known bitcoin blockchain architecture. Though still in evolving stage, the blockchain technology has been able to make an absolute mark in the industries, corporate and governance mechanisms to affirm that it’s part of a definite future. With devices estimate up to 50 billion in ecosystem of Internet-of-Things by 2025, the blockchain technology is soon going to be an integral part of future smart world. The deployment of any blockchain architecture might be able to accomplish the functional requirements as per design but the measurement of desired blockchain performance persists on a lot of parameters which need a balance and fine tuning established on purpose it has been designed for. In current times, transaction commit delays are being observed in bitcoin ecosystem. This paper identifies parameter effects on a bitcoin blockchain and measures the performance vide a bitcoin simulator effecting into tuning parameters like block size, blocks and number of nodes to analyze performance. The tuning effects into blockchain performance has been quantified, analyzed and discussed with focus on measuring and reducing the transaction propagation delays in a bitcoin environment. The paper concludes with heat map modeling plotted on Jupyter notebook with datasets derived.
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