Event-Based Messaging Architecture for Vehicular Internet of Things (IoT) Platforms

Abstract: Internet of Things (IoT) has revolutionized transportation systems by connecting vehicles consequently enabling their tracking, as well as monitoring of driver activities. The IoT platform for most vehicles typically consists of 1) an on-board system consisting of the communication unit, sensors and a set of ECU’s that are interconnected using a CAN network, 2) an off-board system consisting of the applications deployed on the servers (e.g., cloud) that processes the data send by the communication unit over the internet, and 3) mobile devices like a mobile phone or a computer that communicates with the on-board and off-board systems. Such an IoT platform requires a significant amount of data to be send from the on-board system to the off-board servers, contributing to high network usage. There are two main architectural paradigms for sending data: 1) interval based architecture, in which data is send at regular intervals and 2) event based architecture, in which data is send whenever relevant events occur. Currently, (e.g., at Scania), the data is being send at regular intervals, i.e., using an interval based approach. In this case, data is send even if it is not relevant for reporting leading to a wastage of network resources, e.g., when the data does not change considerably compared to the previously sent value. Sending data in an event-based manner, when the data is relevant for reporting, e.g., changes significantly, reduces the network usage when compared to the interval based approach.  In this thesis, we investigate the possibility of using an event based architecture to send data from the on-board system to the off-board system in order to reduce network usage and improve the accuracy of the data available off-board. We first propose an event based architecture for data transfer in the context of Internet of vehicles. We then implement a simulator to evaluate our proposed architecture for the specific case of position data. Finally, we perform extensive experiments varying different parameters and compare, for example, average message size per minute and average off-board error distance. The results show that our event based architecture improves the accuracy of data available at the off-board system, by a careful selection of events. Moreover, we found that our event based architecture significantly decreases the frequency of sending messages, particularly during highway driving, leading to reduced average data transfer rates. Our results enable a customer to perform trade-offs between accuracy and data transfer rates. Future work will aim at implementing the event based architecture on a real platform as well as investigating the possibility of using the event based architecture for more accurate prediction by incorporating additional details such as the final destination of the vehicle and odometer values.