A Domain-Specific Language for the Specification of Adaptable Context Inference

Context-aware mobile applications can benefit from context inference adaptation based on run-time operating conditions, such as battery life or sensor availability. Developing applications with such adaptable behavior, however, is notoriously cumbersome, as developers need to deal with low-level system interfacing and programming issues. In this paper we describe a domain-specific language (DSL) and a middleware infrastructure to support the specification, deployment and maintenance of run-time adaptable context inference processes. We illustrate the benefits of our approach via a case study, highlighting the new abstractions that facilitate the specification of adaptable behavior using different algorithms and the corresponding varying parameter settings, with a specific goal of minimizing the energy while maintanig acceptable end-application performance and accuracy.