An Improvement to Data Service in Cloud Computing with Content Sensitive Transaction Analysis and Adaptation

Currently, cloud computing is one of the significant focuses to the modern ICT technology and service for enterprise applications. Through the advantage of usage of resource visualization, parallel processing, access control, and data service integration with scalable virtual machines, cloud computing can not only reduces the cost and barrier for the automation and computerization to the individuals and enterprises, but also promise lower IT cost, efficient management, high capability for data and user accesses. The virtual machine management and reduction to the corresponding operation overhead, related to virtual machine deploying and clustering, has become the essential issue to the cloud computing comprehensively. And effective and efficient data service has become the key to the bottleneck problem, especially in the cloud environment intermixing with the nature of big data. In this paper, we propose an improvement to data Service in cloud computing with content sensitive transaction analysis and adaptation, which is named ADSC (Adaptive Data Service Coordinator). ADSC manages and monitors the query sequence consisting of data requirement transactions collected from clients/users to the data service virtual machines with big data. Through analyzing with a machine learning awareness algorithm using theory of Fuzzy ART, ADSC detects the similarity, redundancy, and localization of the data accesses, then improve the following transactions by reordering the query sequence or even the virtual machine service re-deployment. ADSC is proposed to benefit enterprise cloud application with more efficient big data and Big Table operation.