Systematic validation of benchmark clustering algorithms for device-to-device communication in disaster environments

Abstract

Clustering algorithms in device-to-device (D2D) communication require reliable benchmarking, especially during disaster scenarios where network behavior heavily depends on modeling assumptions and simulation parameters. However, many common benchmark algorithms are often reused without proper validation, despite incomplete parameter disclosures and limited implementation details in original studies. This raises concerns about fairness, reproducibility, and the credibility of performance comparisons. This study systematically reconstructs and validates popular clustering and routing algorithms for disaster-focused D2D communication, integrating them into a unified simulation framework. Six representative schemes, i.e., LEACH, EAUCA, EEFUC, FQUCR, SCRSO, and PFCRE, are reimplemented based on their original design principles, energy models, and workflows. Each is tested under simulated conditions that closely match those reported in the original references. Key metrics, such as network lifetime, data throughput, and communication latency, are measured and compared with published results to ensure behavioral accuracy. Validation shows that reconstructed algorithms closely mirror their reference behaviors, with deviations mostly between 5% and 13%, within expected stochastic simulation variation. After validation, all benchmarks are run in a standardized environment to facilitate a fair, unbiased comparison while preserving each algorithm's internal behavior. The results demonstrate that systematic benchmark validation enhances reproducibility and reduces evaluation bias in D2D clustering research. The validated implementations and the assessment framework provide trustworthy baseline references for transparent performance evaluation and support the development of robust, energy-efficient D2D communication solutions for disaster response.