A Novel Spherical Fuzzy Schweizer-Sklar Prioritized Framework for Resilient Internet Router Selection in Smart City Digital Infrastructures

Abstract

The digital backbone of any smart city rests upon reliable routing infrastructure, where router reliability governs data throughput for traffic management, public safety, and utility grids. Selecting optimal routers involves intricate trade-offs among bandwidth, security, latency, and cost, all shrouded in expert ambiguity. To methodically resolve this inherent uncertainty, we propose a novel and robust multi-attribute decision-making paradigm anchored in spherical fuzzy sets (SFSs), which capture three-dimensional membership, abstinence, and non-membership grades, seamlessly integrated with Schweizer-Sklar t-norms and t-conorms for flexible parameter-sensitive aggregation. We formally introduce two pioneering operators, namely spherical fuzzy Schweizer-Sklar weighted prioritized aggregation (SFSSWPA) and geometric (SFSSWPG), embedding prioritized hierarchical inter-criteria relationships, thereby ensuring that dominant attributes receive proportionally greater decision weight. The complete multi attribute decision making (MADM) algorithm is validated through a real-world router procurement case study situated within urban critical network infrastructure deployments. Exhaustive comparative assessments against several established fuzzy MADM benchmarks consistently confirm our approach's superior ranking stability and remarkable parameter adaptability.