A Digital-Twin Based Architecture for Software Longevity in Smart Homes

Smart homes usually consist of smart objects (SOs) with limited resources and capabilities, and therefore constrain the complexity of applications that can be performed on them. In particular, updating smart objects within a smart home is a challenging undertaking, as seemingly insignificant updates affect the longevity of the deployment if they cause previously established dependencies to break. In this paper, we propose an architecture that we call Longevity Digital Twins (LDTs) as a strategic counterpart of SOs, aimed at running at the edge, as local to the smart home as possible. With this architecture, the capabilities of a SO can be virtually enhanced to support the software update process in the smart home. In this context, foresighted software management requires both a local capability to describe involved functionalities together with awareness about existing dependencies in this distributed system. Using a simulated smart home environment, we first measure the impact of conventional update strategies and then present the noticeable improvement that LDTs offer to this problem. Going further, we present the analysis of a real-world use case that showcases the potential of LDTs on how it could not only prevent the installation of breaking updates but also extend a SOs capabilities and its overall longevity.