Abstract
Internet of Things (IoT) provides large-scale interoperable service delegations for heterogeneous users through pervasive access. The interconnection of different devices and services in an on-demand and pervasive manner provides seamless responses for different applications. However, a few interconnected devices are stuck into a resource-constraint problem due to limited access and unavailability. This article proposes an interoperable access framework (IAF) for pervasive application services (PAS) for providing robust end-user solutions. The proposed framework balances the accessibility and semantics and its responses for providing seamless interoperability support. In this framework, transfer learning for different limited and free-flow service accessibility is used. The teaching is recurrent for identifying the unavailability of the resources. The process of serving the requests is achieved through interoperable replacement services. It reduces the impact of resource-constraint in the IoT platform, wherein the semantics between unavailability and accessibility is analyzed flawlessly. The proposed framework's performance is verified using the metrics service delay, responses, unavailability, resource utilization, and successful access.