Cloud parallel spatial-temporal data model with intelligent parameter adaptation for spatial-temporal big data

With the fast development of earth observation technology and internet of things technology, the spatial-temporal data can be obtained with higher speed and lower cost, and spatial-temporal big data management with existing spatial-temporal data model has become one of the bottlenecks of spatial-temporal applications such as e-government construction, digital city, and smart city. Cloud parallel spatial-temporal data model with intelligent parameter adaptation for spatial-temporal big data provided in this paper is able to divide a spatial-temporal problem into a lot of subdivided spatial-temporal problems and to map the subdivided problems onto different cloud parallel computing nodes to process. This paper includes the concept, division methods, and mathematical formulas of cloud parallel spatial-temporal data model and provides the method to intelligently find the best parameter of cloud parallel spatial-temporal data model for solving the problem with highest parallel speedup or highest parallel efficiency in cloud parallel computing environment.