Similarity Measure for Interval Neutrosophic Sets and Its Decision Application in Resource Offloading of Edge Computing

Interval neutrosophic sets (INSs), characterized by truth, indeterminacy and falsity membership degrees, handle the uncertain inconsistent information that commonly exists in real-life systems, constitute an extension of interval valued fuzzy set intuitionistic set. The existing works on similarity measures for INSs are mostly constructed distance entropies. Meanwhile, degree is expressed as a single number, even if interval-valued considered. This may lead to loss information. In order cope with these issues, this paper, we introduce new approach constructing using equivalencies. First, based equivalencies aggregation operators, definition equivalence generalized values. Then, framework INSs, propose construction method measure equivalence. could retain more than ever before. addition, according practical situations, one can obtain different similarities selecting parameters Due increase edge computing, it necessary reasonably offload client’s resource assign them server balance usage. Similarity conductive select match client server. Finally, illustrative example verifies proposed find reasonable server, well effectiveness computing application.