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Network connectivity is a fundamental requirement for intervehicle communication and services in VANETs. The fast movement of the vehicles results in rapid changes in network topology generating dynamic variation in network connectivity, which causes dynamic variation in network connectivity. In this paper, we analyze the evolution of the VANETs connectivity based on the realistic data collected by the GPS devices installed on taxis in Shanghai. The study of the evolution characteristics shows that the number of connected components, the size of the giant component, and the connectivity length time series possess strong temporal correlation and long-range dependence. As a result, the short-range dependent processes such as the exponential, normal, or Poisson distributions cannot capture the statistical distribution characteristics. Moreover, all connectivity parameters cannot be described by unimodal distributions. We also conclude that although the whole topology of the VANETs is broken into a large number of small-sized connected components under small transmission radius, the size of the giant component keeps stable when transmission radius reaches the threshold. These results will be helpful to optimize the RSUs deployment and transmission radius to keep the giant component stable and design more efficient strategies to forward the information in VANETs.

An Empirical Study on Evolution of the Connectivity for VANETs Based on Taxi GPS Traces