4.7 Article

Programming Wireless Sensor Networks: Fundamental Concepts and State of the Art

Journal

ACM COMPUTING SURVEYS
Volume 43, Issue 3, Pages -

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/1922649.1922656

Keywords

Languages; Design; Experimentation; Measurement; Performance; Wireless sensor networks; networked embedded systems; programming abstractions; middleware

Funding

  1. Autonomous Province of Trento
  2. Cooperating Objects Network of Excellence (CONET) under EU [FP7-2007-2-224053]
  3. Swedish Foundation for Strategic Research (SSF)

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Wireless sensor networks (WSNs) are attracting great interest in a number of application domains concerned with monitoring and control of physical phenomena, as they enable dense and untethered deployments at low cost and with unprecedented flexibility. However, application development is still one of the main hurdles to a wide adoption of WSN technology. In current real-world WSN deployments, programming is typically carried out very close to the operating system, therefore requiring the programmer to focus on low-level system issues. This not only distracts the programmer from the application logic, but also requires a technical background rarely found among application domain experts. The need for appropriate high-level programming abstractions, capable of simplifying the programming chore without sacrificing efficiency, has long been recognized, and several solutions have hitherto been proposed, which differ along many dimensions. In this article, we survey the state of the art in programming approaches for WSNs. We begin by presenting a taxonomy of WSN applications, to identify the fundamental requirements programming platforms must deal with. Then, we introduce a taxonomy of WSN programming approaches that captures the fundamental differences among existing solutions, and constitutes the core contribution of this article. Our presentation style relies on concrete examples and code snippets taken from programming platforms representative of the taxonomy dimensions being discussed. We use the taxonomy to provide an exhaustive classification of existing approaches. Moreover, we also map existing approaches back to the application requirements, therefore providing not only a complete view of the state of the art, but also useful insights for selecting the programming abstraction most appropriate to the application at hand.

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