The thesis will concentrate on Quality of Service (QoS) trade-offs of Over-the-Air (OTA) updates with a special focus on the use case of updates on a car fleet. Updating software of a car fleet efficiently, requires to have OTA updating techniques that can cope with various problems, like the car fleet’s size and its spatial distribution. It makes sense to compare different techniques for their QoS trade-offs to find the best technique for given circumstances. We wanted to understand the key principles of OTA updates. By researching different techniques for OTA updates and understanding their QoS trade-offs, we have developed a decision model for the best OTA update technique in different cases that appear regarding the update of car fleets. Finally, we wanted to implement some of those techniques for the purpose of analyzing them on QoS aspects. Researching different OTA techniques to find out about their characteristics was a main part of the methodology. Furthermore, we needed to identify which properties were especially important for updating a car fleet. After that, those techniques were analyzed on their QoS aspects. This was achieved by making assumptions on their behavior and by checking them in a simulation environment. In our results we showed 31 techniques that we grouped into four categories and registered them as Architectural Decision Records (ADRs). Amongst those techniques we argued about the trade-offs that are involved and also showed some trade-offs directly in our experimental setup. There we focussed on code dissemination approaches. We found trade-offs between the quality an administrator observes in update completion time and the response times a car driver observes. From the results we concluded which technique fits which use case in updating car fleets.