Wireless sensor networks (WSNs) have grown considerably in recent years and have a significant potential in different applications including health, environment, and military. Despite their powerful capabilities, the successful development of WSN is still a challenging task. In current real-world WSN deployments, several programming approaches have been proposed, which focus on low-level system issues. In order to simplify the design of the WSN and abstract from technical low-level details, high-level approaches have been recognized and several solutions have been proposed. In particular, the model-driven engineering (MDE) approach is becoming a promising solution. In this paper, we present a survey of existing programming methodologies and model-based approaches for the development of sensor networks. We recall and classify existing related WSN development approaches. The main objective of our research is to investigate the feasibility and the application of high-level-based approaches to ease WSN design. We concentrate on a set of criteria to highlight the shortcomings of the relevant approaches. Finally, we present our future directions to cope with the limits of existing solutions.

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Wireless sensor networks (WSNs) comprise resource-constrained (e.g., memory, processing, and energy) sensor nodes that are deployed in different areas and are able to monitor environmental conditions. Simulation has been widely used in order to evaluate the network performance. In this context, software designers need to evaluate, refine, and validate high-level models for WSN applications at early stages of development via simulation tools, in particular for WSN applications supporting energy-harvesting devices. In the present paper, we propose a model-based transformation framework that allows the modeling and simulation of a WSN system supporting energy-harvesting capabilities. In this proposal, we start from a high-level specification based on the UML/MARTE profile, which describes an energyharvesting WSN node. Then a model-to-text (M2T) transformation allows us to generate simulation scripts for analysis purposes by focusing on energy consumption.

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