Data federation through on-demand queries in intelligent transport systems
Oleg K. Golovnin · Journal of Physics Conference Series · 2020
Abstract The paper proposes a federated approach to data integration in intelligent transport systems when data are requested from various sources using the on-demand query technique rather than traditional approach when data are accumulated in a single storage. The proposed approach is designed to reduce the number of data manipulations, thereby increasing the processing speed and reducing the necessary computing resources. The study was carried out on synthetically generated data: 10 data sources are used; each of them consists of 650000 records. Data federation reduces the memory used by an average of 53%, while the time of virtual federal database creation is on average 71% less than the traditional integration approach implementation. The approach to data federation is designed for implementation in intelligent transport systems of a new generation, where it is required to process large amounts of data coming from various heterogeneous sources.