International audienceThe Web of Things (WoT) defines the idea of addressing and requesting any surrounding connected device through web applications. These devices are for a large part, tiny, wireless and mostly battery-powered. Therefore, energy represents a critical limiting resource for their large scale deployment in real life applications, such as smart cities or smart buildings. Consequently, the ability to measure, track and finely profile energy consumption of such devices and correlate it with the application driving the device functionalities is a big challenge to improve the development of WoT embedded applications. In this paper, we present our recent ongoing works on energy consumption measurement of networked embedded applications for the WoT area. More particularly, we focus on measuring energy consumption of the well-known Contiki Operating System HTTP web server using two measurement methods, a simulation based method and a real world software based measurement method. Doing this, we quantify and model the gap existing between the simulation and the real world regarding network embedded applications, such as embedded web servers. Afterwards, we describe our aims in using a real world hardware energy consumption measurement method and profile a home-made embedded web server prototype called Smews. This latter could theoretically improve performances and power consumption of WoT applications relying on TCP/IP protocol

International audienceA huge number of connected objects are expected to be deployed over the coming years in various areas of everyday life. Many of these objects are energy-constrained and depend on a battery. Thus, energy is a critical resource that limits a large scale deployment, and greatly complicates the development of the embedded software on these objects. Hence, the ability to measure and finely profile the power consumption of such devices, and correlate it with the on-board application is a big challenge to improve the software development. Furthermore, common energy patterns can be extracted from the collected energy figures in order to provide guidelines allowing a proactive energy-based development. In this paper, we present an ongoing work about a lightweight framework for energy profiling of embedded applications source code at a functional granularity. It is driven by an on-line hardware-based measurement technique permitting to gather accurate energy figures. The framework is integrated into an energy-centric iterative development cycle allowing fast revalua-tions of the energy consumed by the targeted functions after each source code modification. Afterwards, we describe our future works about overcoming an unlocked state of art issue relative to asynchronous energy consumption profiling

Surrounding autonomous embedded devices are in a constant expansion. The advent and the rise of Internet of Things (IoT) enable these objects to take a giant step forward, especially regarding their large scale deployment in real-world applications of the everyday life. A significant part of these objects are battery-powered and energy-dependent. Thus, energy is a critical resource which greatly complicates the development of the embedded software. By decomposing the energy consumption of a battery-powered IoT device, we can see that peripheral components are the major contributors among the overall consumption. Indeed, these components are exploited and repeatedly used by the object to interact and communicate with its surrounding environment during all the application lifetime. Acquire the expertise to handle accurately, during the development stage, the behaviour of every on-board peripheral component is a big challenge to improve the development of IoT embedded applications.To guide the developer in this task, we propose an automated inference procedure of energy models for peripheral components. An accurate automata-based model of the energy consumption can be generated, with only little efforts from the developer, based on real runtime measurements, providing precise energy figures. The proposed process is focused on a lightweight code generation step and simple analyses of the energy output traces, allowing a quick regeneration of the models in the case of a peripheral component modification. We show the potentials of the proposed procedure by real experiments on real peripherals. The obtained results are satisfactory, and we believe that our proposition is able to enhance the embedded development in an energy-constrained environment.

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