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Supporting Lightweight Adaptations in Context-aware Wireless Sensor Networks

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.
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https://hal.inria.fr/inria-00429708
Contributor : Romain Rouvoy <>
Submitted on : Wednesday, November 4, 2009 - 9:46:52 AM
Last modification on : Wednesday, December 11, 2019 - 2:48:04 PM
Long-term archiving on: : Thursday, June 17, 2010 - 7:18:30 PM

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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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