tracES++: Applying incremental computation to temporal information diffusion analysis for online object traceability

Real-time object traceability records, tracks, and traces objects as they go through the supply chain to ensure product quality, safety, and visibility. Existing traceability systems are challenged with the complexity of supply chain data as objects are continuously transported to different locations, transformed into new objects, or (un)loaded into containers. The existing systems complying with the Electronic Product Code Information Service (EPCIS) global standard capture and share supply chain data across different institutions but are faced with a scalability issue because of the recursive queries brought by object transformations and aggregations. Object traceability is recognized to be closely related to temporal reachability, so temporal graph analysis is proposed to resolve the scalability issue. Despite the resolution, the system enhanced by temporal graph traversal is insufficient for the online monitoring purposes of object traceability because of the redundant computations on a growing temporal graph containing supply chain data. Thus, we propose tracES++, an enhanced EPCIS system that uses a novel incremental temporal graph processing engine to compute temporal reachability. Our system implements triggered queries to eliminate the necessity of sending queries redundantly. Based on our experiments, our system reduces the computation time to update and receive the latest traceability results.