Impacts of Data Integration Approaches on the Limitations of Autonomous Cooperating Logistics Processes

Autonomous cooperating logistics processes are characterized by the ability of intelligent logistics objects to process information, and to render and to execute decisions on their own. In order to do so, these objects need to be able to access data relevant to the decisions to be made. Due to the highly dynamic and heterogeneous nature of the relevant data sources in systems supporting autonomous cooperating logistics processes, the selection and implementation of an adequate data integration approach proves to be a challenging task. Furthermore, the selection, implementation and configuration of different data integration approaches impacts the characteristics of autonomous cooperation in different ways. Aspects such as the timeliness, reactivity, scalability, robustness and adaptability of the data integration mechanisms employed factor into limiting the degree of possible autonomous cooperation. Consequently, this contribution endeavours to systematically analyse the limitations thus imposed by different data integration approaches, and to establish a scheme of categorization for identifying adequate data integration approaches for different degrees of autonomous cooperation.