Multiple queries optimization for data streams on cloud computing

Most of the recent applications such as sensor networks applications, financial applications and click-streams applications generate continuous, rapid, unbounded and time varying datasets that are called data streams. In this paper we proposed a multiple queries optimization for data streams processing on cloud computing (MQODS) frameworks that efficiently execute multiple queries simultaneously on the cloud environment based on their commonalities (common sub-queries). Also we proposed the optimized global plan (OGP) algorithm for data streams' multiple queries over the cloud environment. It generates an optimized global plan for executing multiple continuous queries at the same time on cloud environments. The experimental results prove that the proposed solution MQODS improves the overall performance of data stream processing over multiple queries on the cloud environment.