Simulator code and results for: Energy-Efficient Routing Protocols in IoT Networks: A Narrative Review and Comparative Simulation Study

Simulator code and raw results for the paper Energy-Efficient Routing Protocols in IoT Networks: A Narrative Review and Comparative Simulation Study (M. Haribat and A. Kayed), under revision at Wireless Personal Communications. The Python/NumPy simulator compares six reference implementations of energy-efficient routing under the first-order radio energy model of Heinzelman et al. (2002): FLAT (direct to sink), LEACH, EWC (energy-weighted clustering, inspired by HEED), PEGASIS, SSPT (static shortest-path tree, inspired by RPL) and QL-F (a minimal tabular Q-learning forwarding baseline). EWC, SSPT and QL-F are simplified stand-ins for their design paradigms, not faithful implementations of HEED, RPL or any published learning-based router. The archive contains the simulator (iotsim.py), the experiment driver (run_experiments.py), the script that builds Tables 3–6 and Figures 1–3 (make_tables_figures.py), the raw results of every run reported in the paper (one CSV row per run; 30 seeds per configuration, 6000-round horizon), and the three figures. See README.md for instructions to reproduce each table. Version 1.0.1 fixes a bug in the optional QL-F beacon model: when a node died because it could not pay for its own beacon, its neighbours were still charged for receiving it. The beacon-overhead results were regenerated; no value reported in the paper changes (first-node death, control share and energy per reading are identical in all 450 runs; half- and last-node death changed slightly in some runs). See README.md for details.