Rule based distributed data-service model

This thesis proposes a rule-based data management system for cloud-based heterogenous data service architectures. Management of a scalable data service architecture requires an overarching control mechanism that communicates with a large number of web services quickly and accurately in a reliable manner. The system has to be worked with less time and better efficiency during data update of different services to reach these conditions. Hence, the proposed rule-based system communicates with the web services regularly and processes the designated rules sequentially. One of the common communication methods used to manage the requests in a service architecture is the queuing model. In this thesis, a multilayer service queue model is proposed for the mechanism to work better. In this study, the service management system consists of three main parts; user management, rule management, and rule processing. These parts contain heterogeneous data services needing high security. For this reason, system safety is provided with a two-level protection mechanism which are authentication and authorization. A special application; Graduate School Board Decision Managements System (GSBDMS) is designed implemented for proof of concept. The limits of the rule-based approach are tested with this application. A comparative performance analysis of the modules is given with proper performance metrics. The proposed queuing model is compared with FIFO for its suitability as the communication mechanism. The performance results reveal that the proposed model is better than FIFO in terms of scalability and response time.