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Internet of Things (IoT) has already proven to be the building block fornext-generation Cyber-Physical Systems (CPSs). The considerable amount of datagenerated by the IoT devices needs latency-sensitive processing, which is notfeasible by deploying the respective applications in remote Cloud datacentres.Edge/Fog computing, a promising extension of Cloud at the IoT-proximatenetwork, can meet such requirements for smart CPSs. However, the structural andoperational differences of Edge/Fog infrastructure resist employing Cloud-basedservice regulations directly to these environments. As a result, many researchworks have been recently conducted, focusing on efficient application andresource management in Edge/Fog computing environments. Scalable Edge/Foginfrastructure is a must to validate these policies, which is also challengingto accommodate in the real-world due to high cost and implementation time.Considering simulation as a key to this constraint, various software has beendeveloped that can imitate the physical behaviour of Edge/Fog computingenvironments. Nevertheless, the existing simulators often fail to supportadvanced service management features because of their monolithic architecture,lack of actual dataset, and limited scope for a periodic update. To overcomethese issues, we have developed multiple simulation models for servicemigration, dynamic distributed cluster formation, and microserviceorchestration for Edge/Fog computing in this work and integrated with theexisting iFogSim simulation toolkit for launching it as iFogSim2. Theperformance of iFogSim2 and its built-in policies are evaluated using three usecase scenarios and compared with the contemporary simulators and benchmarkpolicies under different settings. Results indicate that the proposed solutionoutperform others in service management time, network usage, ram consumption,and simulation time.

IFogSim2: An Extended iFogSim Simulator for Mobility, Clustering, and Microservice Management in Edge and Fog Computing Environments