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Programming wireless sensor networks: Fundamental concepts and state of the art

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TLDR
This article presents a taxonomy of WSN programming approaches that captures the fundamental differences among existing solutions, and uses the taxonomy to provide an exhaustive classification of existing approaches.
Abstract
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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TL;DR: In this article, a development methodology that separates IoT application development into different concerns and provides a conceptual framework to develop an application, and a development framework that implements the development methodology to support actions of stakeholders.
References
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Proceedings ArticleDOI

Building up to macroprogramming: an intermediate language for sensor networks

TL;DR: This work proposes an intermediate language, called the token machine language (TML), which provides a layer of abstraction for a lower-level runtime environment, such as TinyOS, intended to capture coordinated activity in a sensor network.
Proceedings ArticleDOI

SenSlide: a sensor network based landslide prediction system

TL;DR: A trip wire installed along the landslide prone areas, and a break in the trip wire due to the falling rocks and debris triggers an alarm, but this is an inexpensive solution for landslide detection and ineffectual in providing warning of the impending landslide.
Proceedings ArticleDOI

Electronic shepherd - a low-cost, low-bandwidth, wireless network system

TL;DR: The ES system, including GPS receivers, UHF radio communication transceivers and GPRS modems, contributes a new approach for low-cost networking and service implementation, not only for the purpose of animal tracking, but also for other applications where objects are to be monitored at a low cost.
Journal ArticleDOI

SensorWare: Programming sensor networks beyond code update and querying

TL;DR: The framework, called SensorWare, defines and supports lightweight and mobile control scripts that allow the computation, communication, and sensing resources at the sensor nodes to be efficiently harnessed in an application-specific fashion, through the use of abstraction services.

Programming Paradigms and Middleware for Sensor Networks

Kay Römer
TL;DR: There is a strong need for programming abstractions that simplify tasking sensor networks, and for middleware that supports such Programming abstractions and middleware.
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