Research of Big Data Space-Time Analytics for Clouding Based Contexts-Aware IOV Applications

With the rapid development of Internet of Things and Big Data analysis, the computing mode of the 21st century is undergoing profound reform. But these technologies bring great challenges such as more multiple-dimensional and more numerous information with wide-area and heterogeneous sensor networks to classical context-aware frameworks at the same time. The IOV (Internet of Vehicles) applications is one kind of the typical IOT (Internet of Things) applications and the data involved in them are more and more big which need more complex querying or analyzing methods. Therefore, we have researched the big data problems in IOV applications and put forward the clouding based big data space-time analytics methods for contexts storing and contexts querying to improve the analysis efficiency of the systems. By these methods, we can improve the capability of the complex IOV applications for dealing the numerous contexts.