Source-Code Analysis of iFogSim for Simulating Distributed IoT Architectures: Coverage, Challenges, and Enhancements

Milliam Maxime Zekeng Ndadji's new arXiv paper performs a structured source-code analysis of iFogSim and iFogSim2, two widely adopted simulators for distributed IoT architectures in fog and edge computing. The study first establishes a taxonomy of ten scientific objectives that motivate IoT simulation, then benchmarks eight competing tools against those objectives, revealing where iFogSim excels and where it falls short. The core contribution is a practitioner-focused guide answering five critical questions: whether iFogSim fits a given architecture, which objectives it covers natively, what modelling challenges arise, what source-code changes would close gaps, and whether co-simulation with other tools can provide comprehensive coverage.

The analysis is grounded in a concrete case study: simulating a four-tier smart emergency response system for resource-constrained urban environments. The experiment uses a 25-node synthetic road topology across four configurations, producing quantitative results including end-to-end alert latency of approximately 205 ms, FPGA-accelerated Dijkstra path computation achieving a 10x speedup over CPU, concurrent incident conflict rates of 75% under dual load, and a remarkable 197x speedup from path-cache acceleration. Seven modelling challenges are documented with source-code-grounded root causes and explicit bias assessments, and the paper concludes with seven developer recommendations as an actionable improvement roadmap for the iFogSim community.