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    一种自适应数据交易软件模型设计技术

    A Self Adaptive Approach to Data Trading Software Modeling

    • 摘要: 在大数据时代,以数据为基本生产要素的数据经济成为推动社会经济发展的创新动力。数据交易是支撑数据流通和创造数据价值的关键环节。然而,如何设计可靠和可维护的数据交易系统面临许多技术挑战性问题。针对这些挑战,本文提出一种自适应数据交易软件模型设计和验证方法。在分析数据交易业务需求的基础上,提出了一种基于Petri网的形式化数据交易自适应软件建模方法,基于Petri网和模型库方法建立数据交易业务流程的形式化模型和控制策略实施技术,Petri网的形式化语义能够有效支持数据交易系统的性质分析。最后,通过仿真实验说明所提方法的有效性和可行性。

       

      Abstract: In the big data era, digital economy takes data as a basic production factor and becomes an innovative driving force for promoting the high-quality development of society and economy. Data trading plays a critical role in supporting the circulation of data resources, and creating data value. However, how to design a reliable and maintainable data trading system faces many technical challenges. Aiming at these challenges, this paper proposes an adaptive approach to modeling and verifying data trading systems. Through analyzing the requirements of data trading business, we propose a formal data trading adaptive software modeling method based on Petri nets, and establish a formal model of data trading business process and control strategy implementation technology based on Petri nets. The formal semantics of Petri nets can effectively support the property analysis of data trading systems. Finally, the simulation results verify the effectiveness and feasibility of the proposed method.

       

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