A self-adaptive context processing framework for wireless sensor networks
Amirhosein Taherkordi, Romain Rouvoy, Quan Le‐Trung, Frank Eliassen · 2008
Wireless sensor networks are increasingly being exploited in ubiquitous computing environments as one of the main platforms for gathering context data. In order to continuously observe the environment context during a long period, the sensor node should be considered itself as a context-aware device having particular contextual parameters, such as residual energy or sample rate. Existing work in the field of context-aware computing mostly considers the sensor node as a context data collector agent, regardless of the concern of the node's context elements. In this paper, we first propose an approach for modeling sensor network context information, and then, we introduce a middleware framework that maps our context model to software components, processes the context data, and implements the context model. For this purpose, we propose the notion of context node, which is the building block of our context processing framework. The proposed solution is exemplified in the shape of a home monitoring application. Using the proposed framework, the sensor application can adapt itself to the current situation in the environment through executing a high-level context model describing both the context information to process and the adaptation actions to perform.