Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains

摘要: In the future, with advent of smart factory era, manufacturing and logistics processes will become more complex, complexity criticality traceability further increase. This research aims at developing a performance assessment method to verify scalability when implementing systems based on key technologies for factories, such as Internet Things (IoT) BigData. To this end, existing research, we analyzed requirements an event schema storing data in MongoDB, document-based Not Only SQL (NoSQL) database. Next, algorithm most representative query defined query-level model, which is composed response times components algorithm. model was solidified linear regression because increase linearly by benchmark test. Finally, case analysis, applied virtual automobile parts logistics. As result study, verified MongoDB-based system predicted point node servers should be expanded case. The proposed can used decision-making tool hardware capacity planning during initial stage construction their operational phase.