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inria-00429708, version 1

Supporting Lightweight Adaptations in Context-aware Wireless Sensor Networks

Amirhosein Taherkordi () a1, Romain Rouvoy () 123, Quan Le-Trung () a1, Frank Eliassen () a1

1st International COMSWARE Workshop on Context-Aware Middleware and Services (CAMS) 385 (2009)

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.

  • a –  NDS research group
  • 1:  University of Oslo (UiO)
  • University of Oslo
  • 2:  Laboratoire d'Informatique Fondamentale de Lille (LIFL)
  • CNRS : UMR8022 – Université Lille I - Sciences et technologies – Université Lille III - Sciences humaines et sociales – INRIA
  • 3:  ADAM (INRIA Lille - Nord Europe)
  • INRIA – CNRS : UMR8022 – Université Lille I - Sciences et technologies
  • Collaboration : EGIDE PHC Aurora
  • Domain : Computer Science/Architecture
  • Internal note : seas
 
  • inria-00429708, version 1
  • oai:hal.inria.fr:inria-00429708
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  • Submitted on: Wednesday, 4 November 2009 09:46:52
  • Updated on: Thursday, 19 July 2012 09:35:36