Fog Computing as a Platform for Intelligent Transportation Applications

Abstract

This chapter discussed the evaluation methodology of the Fog-ROCL strategy. The strategy is evaluated using the different scenarios. Results showed that the Fog-ROCL strategy is more efficient than other strategies. However, the dynamic nature of traffic has a dynamic impact of the fixed RSU setup. It is concluded that a fixed RSU setup cannot cope with the dynamic traffic. Moreover, results revealed that scenarios with high obstacle-density becomes harder to solve using the multi-objective version of the Fog-ROCL strategy. As a result, the next chapter concludes the thesis and discusses some potential research direction for future research work.