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Conference Papers Year : 2009

Supporting Lightweight Adaptations in Context-aware Wireless Sensor Networks


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.
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Dates and versions

inria-00429708 , version 1 (04-11-2009)



Amirhosein Taherkordi, Romain Rouvoy, Quan Le-Trung, Frank Eliassen. Supporting Lightweight Adaptations in Context-aware Wireless Sensor Networks. 1st International COMSWARE Workshop on Context-Aware Middleware and Services (CAMS), Jun 2009, Dublin, Ireland. ⟨10.1145/1554233.1554244⟩. ⟨inria-00429708⟩
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