Cloud Service Selection with Fuzzy C-Means Artificial Immune Network Memory Classifier

Abstract

This paper addresses an cloud service selection model which supports to customize evaluation attributes dynamically. Using expanding the OWL-S Ontology, Cloud service QoS semantics is constructed. The weight of attribute is obtained by the objective and subjective synthetic approach. Based on fuzzy theory and artificial immune network, a new data classification method, named Fuzzy C-Means artificial immune network memory classifier (FCMAINMC), is put forward. According the algorithm, memory antibody collection in which characteristics of service are condensed is abstracted, and each service (antigen) that belongs to some type is also obtained. Using membership matrix and a hundred-mark way, evaluation result which reflects Web quality of service is obtain. The prototype is designed. It is applied to case evaluation fruitfully, and the experiment results are veracious and reliable as well as stable.