During the last two decades, the decentralized execution of business processes has been one of the main research topics in Business Process Management. Several models (languages) for processes' specification in order to facilitate their distributed execution, have been proposed. LSAWfP is among the most recent in this area: it helps to specify administrative processes with grammatical models indicating, in addition to their fundamental elements, the permissions (reading, writing and execution) of each actor in relation to each of their tasks. In this paper, we present a model for a completely decentralized and artifact-centric execution of administrative processes specified using LSAWfP. The presented model puts particular emphasis on actors' views: it then allows the confidential execution of certain tasks by ensuring that, each actor potentially has only a partial perception of the processes' global execution states. The model thus solves a very important problem in business process execution, which is often sidelined in existing approaches. To accomplish this, the model rely on three projection algorithms allowing to partially replicate the processes' global execution states at a given moment, to consistently update the obtained partial states and to deduce new coherent global states. The proposal of these three algorithms, the proof of underlying mathematical tools' stability and a proposal of their implementation, are this paper's main contributions.
翻译:在过去二十年中,业务流程的分散执行一直是业务流程管理的主要研究课题之一。提出了若干程序规格的模型(语言),以便利其分散执行。LASAAWfP是该领域最近的一个:它有助于用语法模型具体行政过程,其语法模型除了其基本要素外,还表明每个行为者与每项任务有关的授权(阅读、写写和执行),每个行为者与其任务的每一项任务有关的授权(阅读、写写和执行)是其基本内容。在本文件中,我们提出了一个完全分散和以奇事本为中心的执行使用LASAAWfP规定的行政程序的模式。我们提出的模型特别强调了行为者的观点:然后通过确保每个行为者对流程的全球执行状态可能只有部分认识,允许机密执行某些任务。LASAAWffP是这一领域的最新例子。因此,该模型解决了业务流程执行中一个非常重要的问题,而这些问题往往与现有方法相平行。要达到这一点,模型依靠三种预测算算法,以便能够在特定时刻部分复制程序的全球执行,不断更新获得的部分状态,并推出新的一致的全球状态。提出这种模型的主要执行工具是:执行工具—— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— 3 —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— —— ——