This paper develops a generic approach to model interactive control loops in the Internet of Things (IoT) environments. We take advantage of interactive MAPE-K loops to enable architectural self-adaptation. The system’s architectural setting is aligned with the adaptation goals and with the components run-time situation and constraints. We introduce an integrated framework for IoT Architectural Self-adaptation ( IAS) were functional control elements are in charge of environmental adaptation and autonomic control elements handle the functional system’s architectural adaptation. A Queuing Networks (QN) approach was used for modeling the IAS. The IAS-QN can model control levels and their interaction to perform both architectural and environmental adaptations. The IAS-QN was modeled on a smart grid system for the Melle-Longchamp area (France). Our architectural adaptation approach successfully set the propositions to enhance the performance of the electricity transmission system. This research is a part of CPS4EU European industrial innovation project.