Evaluation and its derived classification in a Server-to-Client architecture based on the fuzzy relation inequality

• Published in: Fuzzy optimization and decision making Vol. 22; no. 2; pp. 213 - 245
• Main Authors: Xiao, Gang, Hayat, Khizar, Yang, Xiaopeng
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2023; Springer Nature B.V
• Subjects: Artificial Intelligence; Calculus of Variations and Optimal Control; Optimization; Classification; Data transmission; Equivalence; Evaluation; Fuzzy sets; Inequalities; Inequality; Mathematical Logic and Foundations; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Optimization models; Probability Theory and Stochastic Processes; Servers; Streaming media; Fuzzy relation equation; Max-min composition; Evaluation score; Division of the solution set; Fuzzy relation inequality
• ISSN: 1568-4539; 1573-2908
• DOI: 10.1007/s10700-022-09390-3

Server-to-Client network system is one of the most important architectures for data transmission. Fuzzy relation inequalities have been introduced to manage the quality levels in such system. In most existing works, relevant optimization models have been studied for providing some optional schemes to the manager. In this paper, we first define the concept of evaluation score for the server, embodying the service capability for supplying its local resources to the clients. Then the servers could be ordered according to their evaluation scores. Some interesting properties of the evaluation score vector are investigated. Applying our proposed evaluation model, we further construct an equivalence relation, based on which the complete solution set of the fuzzy relation inequalities could be divided into several equivalence classes. In such classification, each equivalence class corresponds to a unique evaluation score vector. Numerical examples are provided to illustrate our proposed evaluation model and classification method.