A collaborative cloud service for big data analysis using trust calculation scheme

Abstract

Cloud service collaboration has been chosen by businesses as an effective solution to the prime challenges in cloud computing services, especially regarding the data storage. This enables effective interaction among the users of multiple occupants of a cloud provider to work in association. During collaboration, the users might have to share, access and use files and resources belonging to themselves and other collaborating members. These resources may include the most sensitive data and computing tasks delivered by various users to cloud service properties. Cloud service providers must earn the trust from their users before enabling this. On the other hand, multiple secure transactions between users and service providers on their platform help the service providers to gain trust in business and to mark their business as reliable. Hence implementing trustworthy and collaborative cloud service is the fundamental demand along with ensuring increased speed and reduced overhead, especially in the case of big data. Evaluation of trust values of the `cloud computing schemes thus deserves critical attention and various trust models have been proposed each with its own features and limitations. Evaluation of the effectiveness of the trust models gains significance in this context which forms the basis motivation of this work. Here, we focus on the critical evaluation of the recently proposed fast and parallel trust computing model developed for big data analysis. The evaluation of the above said model on selected cloud collaborative service environments is carried out and the effectiveness of the model in each environment is analysed based on several parameters. We also use the model to estimate the trust value of selected cloud services under separate time bands and look forward for the significant remarks on time based evaluation.