Optimization and adaptation of situation-aware applications based on workflow fragments

到目前为止，在项目过程中开发的SitOPT解决方案能够动态、自主地适应工作流程，以适应当前的情况。在动态环境中，例如生产环境中，可以以适当的方式调整工作流执行以适应不断变化的和可能不可预见的情况。SitOPT正在寻求一种集中的方法来控制动态环境，这种方法并不适用于所有的应用领域。在延续应用程序中，将开发DiStOPT（分布式SitOPT）概念，并对已开发的概念进行扩展。DiStOPT的目标是在去中心化的基础上监控分布式动态环境，以便在运行时自动和全局地适应涉及多个参与者并以编排形式建模的流程。例如，物联网或工业4.0环境可以被有效监控，相关工作流程可以自主调整。可伸缩性、可用性和近实时处理在这些分布式场景中扮演着重要的角色，因此必须包含明显超越上一个项目机制的新概念。扩大研究项目DiStOPT的目标是开发允许分散监测和适应分布式动态环境的概念和方法。特别是，涉及多个参与者的流程应该在运行时根据情况自动在全局透视图中进行调整。为了监控具有高效率要求的现代物联网或工业4.0环境，SitOPT组件的灵活部署旨在检测分布式、多样化系统环境中发生的情况。例如，这些包括各种云类型，如边缘云、私有云或公共云。边缘云指的是一个系统环境，它与上下文感知传感器之间的通信路径非常短。因此，数据可以在尽可能靠近传感器的地方进行处理，从而可以避免长时间的通信路径。这可以提供近乎实时的数据处理情况。然而，非时间关键型、计算密集型的计算可以外包到私有或公共云环境中。为了实现这一点，必须在分布式系统上创建基于多云的SitOPT组件管理。为了以协作的方式调整流程，必须开发情境自适应编排的概念，从而将工作流适应提升到更高的水平。必须考虑个别伙伴发生的当地情况以及影响所有参与伙伴的全球情况。

The solution SitOPT, which has been developed in the course of the project so far, enables dynamic, autonomous adaptation of workflows to present situations. In a dynamic environment, e.g. a production environment, it is possible to adapt a workflow execution in an appropriate manner to changing and possibly unforeseen situations. SitOPT is pursuing a centralized approach to the control of dynamic environments, which is not suitable for all application domains.In the continuation application, the concept DiStOPT (Distributed SitOPT) is to be developed, in which the developed concepts are extended. The objective of DiStOPT is to monitor distributed dynamic environments on a decentralized basis, in order to adapt processes, which involve several participants and are modeled in the form of choreographies, automatically and globally at runtime. For example, Internet of Things or Industry 4.0 environments can be efficiently monitored and related workflows can be adapted autonomously. Scalability, availability and near-real-time processing play a fundamental role in these distributed scenarios and must therefore be covered by new concepts that clearly go beyond the mechanisms of the previous project.The objective of the expanded research project DiStOPT is to develop concepts and methods that allow decentralized monitoring and adaptation of distributed dynamic environments. In particular, processes that involve more than one participant should be automatically adapted in a global perspective at runtime depending on the situation. In order to monitor modern Internet of Things or Industry 4.0 environments with high efficiency requirements, a flexible deployment of the SitOPT components is designed to detect occurring situations in distributed, diverse system environments. These include, for example, various cloud types, such as edge cloud, private cloud, or public cloud. An edge cloud refers to a system environment that has very short communication paths to context-aware sensors. As a result, data can be processed as close as possible to the sensor and thus long communication paths can be avoided. This allows near-real-time processing of the data to provide situations. Non-time-critical, computationally intensive calculations can, however, be outsourced in private or public-cloud environments. In order to achieve this, a multi-cloud-based management of the SitOPT components on distributed systems must be created. In order to adapt the processes in a collaborative manner, concepts for situation-adaptive choreographies have to be developed which bring the workflow adaptation to a higher level. Both local situations that occur with individual partners as well as global situations affecting all participating partners must be considered.