Akademik Məlumat İdarəetmə Sistemi
COMPUTER STANDARDS & INTERFACES, vol.96, 2026 (SCI-Expanded, Scopus)
Efficient Task Mapping Techniques (TMTs) play a crucial role in enhancing the security of 3-Dimensional Network-on-Chip-based Multiprocessor Systems-on-Chip (3D-NoC-based MPSoCs) architectures deployed in IoT environments by optimizing resource allocation and minimizing vulnerabilities in communication. However, selecting the secure TMT is a fresh challenge due to the difference in importance of evaluation criteria, data variation among these criteria, trade-offs, and uncertainty. This study aims to determine the secure TMT utilizing the Multicriteria Decision-Making (MCDM) framework. Our methodology is separated into three phases. Firstly, this paper establishes a decision matrix for TMT, considering ten criteria and ten alternatives. Secondly, the Pythagorean Fuzzy Set with Weighted Fuzzy Judgment Matrix (PYS-FWJM) method is proposed to determine the weights of ten evaluation criteria. Moreover, the MULTIMOORA-Borda method is employed to construct the TMT selection model based on ten key alternatives. The criteria weighting results highlight that communication overhead (0.1038), thermal management (0.1021), and cost-effectiveness (0.1029) are the most critical factors influencing TMT selection, emphasizing the importance of efficient data transfer, thermal stability, and resource optimization. The MULTIMOORA-Borda ranking results indicate that Dynamic Voltage and Frequency Scaling (DVFS) ranks as the top TMT, while the Branch-and-Bound is the least effective TMT. The framework's effectiveness and robustness are verified through sensitivity analysis and the Spearman technique. This research offers a structured and scalable evaluation model that enables researchers and practitioners to enhance TMT efficiency while ensuring robust security protection in IoT-driven environments. The outputs of this study contribute to achieving SDG 12 by promoting sustainable IoT.