The number of connected devices — also known as Internet of Things (IoT) — is exponentially increasing. Such sensors and devices also appear in transportation systems giving some intelligence to roads, equipment and vehicles. Nowadays, it is possible to communicate with the environment in order to have better everyday services. Furthermore, the number of registered — public or private — Electric Vehicle (EVs) is continuously increasing. These vehicles, equipped with large battery, need to be charged and so, have a significant impact on power grids. However, these EVs can also be seen as energy sources. It is therefore important to be able to plan both the charge and discharge of EVs. Including these vehicles into Vehicle-to-Grid technology is a way to efficiently manage such pools of batteries. But, as a consequence, grid requires to have almost real-time data on these vehicles and especially their battery status. This paper studies an optimized data aggregation method for a fleet of electric buses. Each bus provides different type of information with different priority level. The efficiency of the studied method was evaluated with a simulation platform developed with ns-3. Simulation results — based on real route and bus stop positions — show that an optimal buffer size has been found to both satisfy transmission delays and optimize communications.