A BPSO-ANN model for Trust Prediction of Cloud Services
Manjubala Bisi, Shubham Patel · 2019 Global Conference for Advancement in Technology (GCAT) · 2019
Trustworthiness prediction of cloud services is a challenging task in cloud environment. Introduction of new services affect the service quality and user satisfaction. Intelligent techniques are used to predict the trust rate of a cloud service based on its quality of service attributes. Artificial Neural Network(ANN) is used to predict the quality of cloud service using some quality attributes. Particle Swarm Optimization (PSO) technique is used to train ANN. The selection of quality attributes is done using Binary Particle Swarm Optimization (BPSO) technique. The experiments are performed on QWS data set. It is observed from the experiments that proposed BPSO model for attribute selection and PSO for ANN training provides better prediction accuracy.