Fog Computing is a new paradigm aiming at decentralizing the Cloud by geographically distributing away computation, storage and network resources as well as related services. In order to design, develop, deploy, maintain and evolve Fog systems, languages are required for properly modeling both their entities (e.g., infrastructures, topologies, resources configurations) and their specific features such as the locality concept, QoS constraints applied on resources (e.g., energy, data privacy, latency) and their dependencies, the dynamicity of considered workloads, the heterogeneity of both applications and devices, etc. This paper provides a detailed overview of the current state-of-the-art in terms of Fog modeling languages. We relied on our long-term experience in Cloud Computing and Cloud Modeling to contribute a feature model describing what we believe to be the most important characteristics of Fog modeling languages. We also performed a systematic scientific literature search and selection process to obtain a list of already existing Fog modeling languages. Then, we evaluated and compared these Fog modeling languages according to the characteristics expressed in our feature model. As a result, we discuss in this paper the main capabilities of these Fog modeling languages and propose a corresponding set of open research challenges in this area. We expect the presented work to be helpful to both current and future researchers or engineers working on/with Fog systems, as well as to anybody genuinely interested in Fog Computing or more generally in distributed systems.