Poster: Edge-Assisted Over-the-Air Software Updates.

The exploration of software Over-the-Air (OTA) updates for au-tomotive applications is currently very limited. Our work intro-duces an edge-assisted framework for automotive OTA updates that carefully accounts for various factors, including different soft-ware models in vehicles, communication distances, and cluster sizes. We present valuable insights using key evaluation metrics like update speed, data transmission efficiency, and success rate, accompanied by a thorough scalability analysis. Our research in-volves three distinct vehicle software models: ResNet-18 (46.8 MB), ResNet-50 (102.5 MB), and Faster R-CNN (175.2 MB). These mod-els are used to evaluate update performance across eight distance categories ranging from 0 to 21 meters with a 3-meter interval. We also utilize diverse computing platforms to assess the success rate and conduct a comprehensive scalability analysis. This innovative approach significantly advances our understanding and practical implementation of OTA updates in the automotive field.