Synthetic generation of cellular network positioning data

A Spatio-Temporal Simulation Model for Incremental Clustering in Massive Moving Objects Data Set

“…When a vehicle enters the system and begins to travel along a trajectory, the simulation model initiates a simulated vehicle entity at the starting point, which then parallels the entire vehicle's movement through the sequence of intersections until arriving at the final point. This vehicle entity is delayed at the final point for a period of [5][6][7][8][9] hours, after which it returns to the starting point along the previously-used trajectory or via another defined trajectory (in the proposed model, we defined delay as uniform distribution with parameters minDelay and maxDelay). This suggested trajectory-switching procedure is executed by means of a predefined trajectory probability matrix.…”

A prototype of synthetic data generator

“…Todo esto con el propósito de generar, sistemáticamente, conjuntos de datos sintéticos que permitan evaluar algoritmos, herramientas y aplicaciones. Varias herramientas se han creado con este propósito [2][3][4][5][6][7][8][9][10].…”

Hermoupolis: A Trajectory Generator for Simulating Generalized Mobility Patterns

“…These mobility patterns imply the different profiles of movement that we want to reproduce, covering many of the examples cited earlier. On the other hand, related work includes data generators simulating either movement in free space, including GSTD [15], CENTRE [4] and C4C [11], or network-constrained movement, including Brinkhoff [1] and BerlinMOD [2]. Although the above generators present very interesting features, they cannot be considered pattern-aware, in the sense that we described earlier.…”