Processed ASUNA-based data and Python code for adaptive beacon-controlled time synchronization in mobile underwater acoustic sensor networks

This dataset contains processed measured-data-driven evaluation files and Python code used to generate the performance results for the manuscript “Adaptive Beacon-Controlled Time Synchronization for Mobile Underwater Acoustic Sensor Networks.” The evaluation uses the public ASUNA BerlinMultimodal-06-16 underwater acoustic network dataset as measured input for packet-success behavior, topology variation, node-location information, packet-loss estimation, and time-varying link conditions. The raw ASUNA dataset is not claimed as original work by the author. This deposited dataset contains only the processed CSV files, figure-generation data, and Python scripts used to evaluate the proposed ACB-TS method. The files include processed synchronization result data for RMS synchronization error, adaptive beacon control, energy consumption, control-packet overhead, convergence time, mobility variation, packet-loss variation, and relative reduction compared with fixed-beacon synchronization. The Python code can be used to reproduce the CSV files and figures reported in the manuscript.