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In this work, we consider runtime adaptation in networked embedded systems with tight real-time constraints. For such systems, we aim to adapt the placement of software components on networked hardware components at runtime without violating real-time constraints. We develop constraints for such an adaptation process and show the applicability to networked embedded systems like automotive in-vehicle networks. Then, we analyze two approaches for finding solutions in the resulting search space for adaptations, one based on planning algorithms and the other based on constraint solving. While planning approaches start from the current configuration and aim to find a migration sequence and a valid configuration, constraint solving approaches first find solutions and then check for a possible migration sequence. Based on simulations for the automotive domain, we show that approaches based on planning algorithms scale poorly, while constraint solving approaches can find solutions effectively.