User Preference Based Cumulative Trust (UPBCT) Computation Model

Cloud Computing is the biggest buzz word in the Computer and Information Technology industries. Almost every IT organization has adopted cloud computing technologies. There are multiple Cloud Service Providers (CSP) in the market like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), IBM Cloud (Kyndryl) and many more. Every CSP provides various cloud services to Cloud Users (CU). It is a big challenge today for cloud users to decide on which CSP will be suitable for their requirements. Trust values for cloud services helps cloud users to choose the most suitable cloud service and CSP. Trust computation has several methodologies like reputation based, SLA verification based, self-assessment based, policy based, societal trust based, and evidence based. Among all these methodologies, evidence-based trust computation is considered as the effective and most trustworthy as it computes the trust values based on QoS attributes of the cloud services. We have studied many of evidence-based models proposed by various researchers. Among many we found that the approach of weightage-based normalization of QoS attribute values is more effective and accurate while calculating the trust values. Also, we found that these models are missing on what user is expecting with respect to values of QoS attributes. Accordingly, in this paper we have proposed a User Preference Based Cumulative Trust (UPBCT) computation model which is evidence-based, follows weightage-based normalization of QoS attribute values approach, and takes in account the user preferred values for QoS attributes. The results support the efficiency of the proposed model compared to other models, helps cloud users to choose better cloud service as per their requirements and helps CSP with the desired value for QoS attributes so that they can enhance their cloud services to meet those desired values of QoS attributes and increase the trust values of their cloud services.