Enhancing query processing on stock market cloud-based database

Abstract

Cloud computing is rapidly expanding because it allows users to save the development and implementation time on their work. It also reduces the maintenance and operational costs of the used systems. Furthermore, it enables the elastic use of any resource rather than estimating workload, which may be inaccurate, as database systems can benefit from such a trend. In this paper, we propose an algorithm that allocates the materialized view over cloudbased replica sets to enhance the database system's performance in stock market using a Peerto-Peer architecture. The results show that the proposed model (MVCRS) improves the query processing time and network transfer cost by distributing the materialized views over cloudbased replica sets. Also, it has a significant effect on decision-making and achieving economic returns.