基于oracle的流程自动化在DLT主导的生态系统中应用于德国水路运输

T. Osterland, T. Rose
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引用次数: 3

摘要

分布式账本技术(DLT)旨在确保交易和流程管理的正确性和完整性。分类帐保存数据交易的记录,并确保与数据相关的流程的正确执行。通过建立共识,可以实现过程和各方之间的一致性。然而,当大量数据需要确认时,可伸缩性是一个主要问题。当对具有大量数据的现有业务流程进行数字化时,可伸缩性成为一个关键目标。因此,信息压缩的技术手段成为一项至关重要的资产。本文提出了一种新的数据聚合方法。一方面,汇总数据只是为了在分类帐上维护汇总的审计证书。另一方面,聚合的原始数据的来源可以被跟踪和正确证明。因此,业务关系中信息交换的审计服务可以扩展,而供应商方的原始数据必须不被详细披露。我们提出了一种新的架构,用于高效的数据聚合,同时确保智能合约及其处理相关过程数据的主要功能。德国水路运输作为评估情景。此外,分散的身份管理被引入作为我们支持dlt的业务协作生态系统的锚定元素。因此,对于M2M经济体来说,保护个人数据的主权和安全是可以保证的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Oracle-based process automation in DLT dominated ecosystems with an application to German waterway transportation
Distributed ledger technology (DLT) has been designed to ensure the correctness and integrity of transaction and process management. A ledger maintains records of data transactions as well as assures the correct execution of processes attached to data. Consistency across processes and parties is achieved by means of consensus building. However, scalability is a major concern when and significant amounts of data need confirmation. When digitalizing existing business processes with serious amounts of data, scalability becomes a pivotal objective. Hence, technical means for information compression become a vital asset. This paper presents a novel approach for data aggregation. On the one hand, data are aggregated in order to merely maintain an audit certificate of the aggregate on the ledger. On the other hand, provenance of raw data aggregated can be traced and proven correctly. Hence, audit services for information exchange in business relationships can scale, while raw data of supplier parties must not be unveiled in detail. We present a novel architecture for efficient data aggregation, while ensuring smart contracts and their main functionality of processing relevant process data. German waterway transportation serves as evaluation scenario. Moreover, decentral identity management is introduced as anchor element of our DLT-enabled ecosystem for business collaboration. Hence, preserving sovereignty and safety of personal data can be assured for M2M economies.
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