iFogSim is a simulator for modeling and simulating resource management techniques in IoT, Edge, and Fog computing environments. The paper presents iFogSim, a simulation tool that enables the evaluation of resource management policies in terms of latency, network congestion, energy consumption, and cost. The simulator models IoT and Fog environments and allows the comparison of different resource management policies. Two case studies are presented to demonstrate the modeling of an IoT environment and the comparison of resource management policies. The scalability of iFogSim in terms of RAM consumption and execution time is also verified under different scenarios. The paper discusses the architecture of iFogSim, its design and implementation, and presents two case studies to demonstrate how one can model an IoT environment and plug in and compare resource management policies. The paper also evaluates the scalability of iFogSim in terms of memory consumption and simulation execution time. The paper is structured as follows: A formal definition of Fog computing, its concepts and benefits are presented in Section 2. Section 3 discusses the architecture of iFogSim followed by its implementation details, sample resource management policies, and a generic simulation recipe in Section 4. Case studies along with their application models and network topologies are expounded in Section 5. Section 6 presents results of scalability tests on iFogSim and compares two basic resource management policies considering metrics such as latency, energy consumption and network usage. Finally, Section 8 concludes the paper and discusses the future directions.iFogSim is a simulator for modeling and simulating resource management techniques in IoT, Edge, and Fog computing environments. The paper presents iFogSim, a simulation tool that enables the evaluation of resource management policies in terms of latency, network congestion, energy consumption, and cost. The simulator models IoT and Fog environments and allows the comparison of different resource management policies. Two case studies are presented to demonstrate the modeling of an IoT environment and the comparison of resource management policies. The scalability of iFogSim in terms of RAM consumption and execution time is also verified under different scenarios. The paper discusses the architecture of iFogSim, its design and implementation, and presents two case studies to demonstrate how one can model an IoT environment and plug in and compare resource management policies. The paper also evaluates the scalability of iFogSim in terms of memory consumption and simulation execution time. The paper is structured as follows: A formal definition of Fog computing, its concepts and benefits are presented in Section 2. Section 3 discusses the architecture of iFogSim followed by its implementation details, sample resource management policies, and a generic simulation recipe in Section 4. Case studies along with their application models and network topologies are expounded in Section 5. Section 6 presents results of scalability tests on iFogSim and compares two basic resource management policies considering metrics such as latency, energy consumption and network usage. Finally, Section 8 concludes the paper and discusses the future directions.