BerlinMOD : a benchmark for moving object databases
This document presents a method to design scalable and representative moving object data (MOD) and a set of queries for benchmarking spatio-temporal DBMS. Instead of programming a dedicated generator software, we use the existing Secondo DBMS to create benchmark data. The benchmark is based on a simulation scenario, where the positions of a sample of vehicles are observed for an arbitrary period of time within the street network of Berlin. We demonstrate the data generator's extensibility by showing how to achieve more natural movement generation patterns, and how to disturb the vehicles' positions to create noisy data. As an application and for reference, we also present Ørst benchmarking results for the Secondo DBMS. Such a benchmark is useful in several ways: It provides well-deØned data sets and queries for experimental evaluations; it simpliØes experimental repeatability; it emphasizes the development of complete systems; it points out weaknesses in existing systems motivating further research. Moreover, the BerlinMOD benchmark allows one to compare diÆerent representations of the same moving objects.
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