GPU parallel algorithms for reporting movement behaviour patterns in spatiotemporal databases

• Autores: Ignacio Valladares Cereceda
• Directores de la Tesis: Marta Fort (dir. tes.), J. A. Sellarès i Chiva (dir. tes.)
• Lectura: En la Universitat de Girona ( España ) en 2013
• Idioma: inglés
• Tribunal Calificador de la Tesis: Ferran Hurtado Díaz (presid.), Gustavo Ariel Patow (secret.), Kevin Buchin (voc.)
• Materias:
  • Matemáticas
    • Ciencia de los ordenadores
      • Informática
• Enlaces
  • Tesis en acceso abierto en: TDX
• Resumen

  • In this thesis we treat and solve various problems related to movement pattern detection by designing and implementing parallel algorithms using the GPU. We first propose a GPU pipeline based algorithm to report the ’Popular places’ pattern. Then, we study the problem of reporting all subtrajectory clusters of a trajectory. To measure similarity between curves we choose the Fréchet distance. Finally we solve the ’Flock pattern’. To this aim, we present two algorithms to solve two problems related with the ’Flock pattern’: finding the maximal sets of a family and intersecting two families of sets. The GPU parallel algorithms proposed to solve these two problems are later used for reporting flock patterns