tracES++: Applying Incremental Computation to Temporal Information Diffusion Analysis for Online Object Traceability

Real-time object traceability is crucial for ensuring product quality, safety, and visibility within and across institutions within the supply chain. While traceability systems comply with the Electronic Product Code Information Service (EPCIS) global standard for interoperability, they face scalability challenges due to the complexity of supply chain data, including the recursive queries brought by continuous object transformations and (dis)aggregations. Recognizing the close relationship between object traceability and temporal reachability, temporal graph analysis was integrated into an EPCIS System to resolve the scalability issue. However, the graph-enabled EPCIS system fails to meet the demands of online monitoring due to the redundant computations on a growing temporal graph containing supply chain data. Thus, we propose tracES++, an enhanced EPCIS system featuring a novel incremental temporal graph processing engine that efficiently computes temporal reachability. tracES++ updates the traceability results incrementally when the underlying temporal graph changes, avoiding recomputations from scratch. Moreover, it leverages triggered queries to eliminate the necessity of redundant query transmissions. Experimental results demonstrate reductions in the number of queries and the computation time to receive the latest traceability results.