Differential Privacy-Driven Trust-Based Fuzzy Clustering with Adaptive Ring Optimization for Secure Wireless Sensor Networks

This dataset supports the research work titled “Differential Privacy-Driven Trust-Based Fuzzy Clustering with Adaptive Ring Optimization for Secure Wireless Sensor Networks.” The dataset contains all simulation files, configuration scenarios, and MATLAB implementations used to evaluate the proposed clustering framework in Wireless Sensor Networks (WSNs).
The dataset includes NetSim 14.02 simulation files corresponding to three different network density scenarios designed to evaluate scalability and performance under varying node distributions. The first scenario consists of 64 sensor nodes deployed in a 300 × 300 m² network field, the second scenario includes 100 sensor nodes deployed in the same 300 × 300 m² region, and the third scenario contains 200 sensor nodes deployed in a larger 500 × 500 m² network field. Each scenario file contains complete network topology configurations, routing parameters, and communication settings required to reproduce the simulation environment.
In addition to NetSim scenario files, the dataset provides MATLAB source code files used to implement the proposed fuzzy clustering, trust evaluation, differential privacy mechanism, and adaptive ring optimization techniques. These MATLAB files include algorithms for cluster formation, cluster head selection, trust computation, privacy-preserving data aggregation, and performance metric evaluation.
The dataset enables full reproducibility of experimental results presented in the study, including energy consumption analysis, clustering efficiency, and network stability comparisons with existing protocols. Researchers can use these files to validate results, extend the proposed model, or conduct comparative performance studies in secure and energy-efficient Wireless Sensor Network environments.