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Designing integrated electronic control units (ECU) in the automotive domain is challenging especially when legacy sub-systems are involved. Nevertheless, important design decisions have to be made at early design stages when some performance parameters of new sub-systems may not be validated yet. To account for uncertainty in the system development we use statistical modeling and discrete event simulation to perform sensitivity analysis from an average-case perspective. Average-case analysis is useful if performance aspects during normal system operation are of interest. The simulation model we implemented enables us to conduct holistic sensitivity analyses of systems consisting of multiple controllers, field-busses, sensors, actors, and applications. Applications are modeled as signal chains traversing the system model experiencing delay in each node along the predefined path. We present the strength of our approach by analyzing the latency of a distributed application in case of an asynchronous, synchronous, and event-triggered integrated ECU context. The results show that clock drift may result in high signal latencies in asynchronous ECUs and synchronous ECUs are superior in terms of signal latency and jitter. Event-triggered ECUs have to be designed carefully and come with trade-offs between performance of the legacy system and new applications.