Efficiently scheduling computational jobs with data-sets dependencies is one of the most important challenges of fog/edge computing infrastruc-tures. Although several strategies have been proposed, they have been evaluated through ad-hoc simulator extensions that are, when available, usually not maintained. This is a critical problem because it prevents researchers to-easily-conduct fair evaluations to compare each proposal. In this short paper, we propose to address this limitation by presenting the first elements of a common simulator. More precisely, we describe an ongoing project involving academics and a high-tech company that aims at delivering a dedicated tool to evaluate scheduling policies in edge computing infrastructures. This tool enables the community to simulate various policies and to easily customize researchers/engineers' use-cases, adding new functionalities if needed. The implementation has been built upon the Batsim/SimGrid toolkit, which has been designed to evaluate batch scheduling strategies in various distributed infrastruc-tures. Although the complete validation of the simulation toolkit is still ongoing , we demonstrate its relevance by studying different scheduling strategies on top of a simulated version of the Qarnot Computing platform , a production edge infrastructure based on smart heaters.