Engineering contextual knowledge for autonomic pervasive services

In this paper, we identify the key software engineering challenges introduced by the need of accessing and exploiting huge amount of heterogeneous contextual information. Following, we survey the relevant proposals in the area of context-aware pervasive computing, data mining and granular computing discussing their potentials and limitations with regard to their adoption in the development of context-aware pervasive services. On these bases, we propose the W4 model for contextual data and show how it can represent a simple yet effective model to enable flexible general-purpose management of contextual knowledge by pervasive services. A summarizing discussion and the identification of current limitations and open research directions conclude the paper.