Supporting lightweight adaptations in context-aware wireless sensor networks

  • Authors:

  • Amirhosein Taherkordi;Romain Rouvoy;Quan Le-Trung;Frank Eliassen

  • Affiliations:

  • University of Oslo, Oslo, Norway;University of Oslo, Oslo, Norway and INRIA-USTL-CNRS, Parc Scientifique de la Haute Borne, Villeneuve d'Ascq;University of Oslo, Oslo, Norway;University of Oslo, Oslo, Norway

  • Venue:
  • Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009)
  • Year:
  • 2009

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Abstract

Context-aware environments are being populated with Wireless Sensor Networks (WSNs), observing sensory context elements, and adapting their behavior accordingly. Although adaptation has been known as a common approach for addressing context-awareness, the resource-scarceness of WSNs raises the requirements for lightweight adaptations. The related work in the field of updating WSN applications mostly focuses on i) developing techniques to distribute a monolithic program to a set of nodes or ii) reprogramming the whole sensor nodes, which have been seen as impractical and inefficient solutions for a large number of sensors deployed in inaccessible regions. In this paper, we propose a new software development paradigm, which revisits the way WSN applications are designed in order to optimize the adaptation process. Our approach promotes lightweight adaptation by proposing a component model reconfiguring modules at the behavior-level instead of component-level. We evaluate this model by analyzing a sample reconfigurable application atop Contiki---a popular operating system for sensor nodes. The preliminary analysis shows that our adaptation approach is efficient in terms of energy consumption, memory usage, and reconfiguration complexity.