An Intelligent Data Service Framework for Heterogeneous Data Sources

Heterogeneous data on distributed computing sources are growing day by day. To manage the data from the distributed sources into a distinct type of application like mobile, cloud, desktop, web etc. is a challenging issue in the global information systems, particularly for cooperation and interoperability. This paper proposes a Data Service Framework, which integrates the data from distributed sources such as databases, Simple Object Access Protocol (SOAP) based web services and flat files, and performs create, read, update and delete (CRUD) operations on it through Representational State Transfer (REST) services over the Hyper Text Transfer Protocol (HTTP). The proposed data service framework also supports java database connectivity (JDBC). Detailed description of the proposed framework and experimental results are reported in this paper.

[1]  Cesare Pautasso.  On Composing RESTful Services , 2009, Software Service Engineering.

[2]  Cătălin Strimbei,et al.  Smart Data Web Services , 2012 .

[3]  Fakhri Alam Khan,et al.  Efficient data access and performance improvement model for virtual data warehouse , 2017 .

[4]  Jun Sawamoto,et al.  Database virtualization technology in ubiquitous computing , 2009, 2009 International Conference on Innovations in Information Technology (IIT).

[5]  Jun Sawamoto,et al.  Virtualization Technology for Ubiquitous Databases , 2010, 2010 International Conference on Complex, Intelligent and Software Intensive Systems.

[6]  Xiaohui Zhang,et al.  Data Management in Structural Engineering Experiment Grid , 2010, 2010 Fifth Annual ChinaGrid Conference.

[7]  Fakhri Alam Khan,et al.  Aggregated provenance and its implications in clouds , 2018, Future Gener. Comput. Syst..

[8]  Daniel Szepielak.  REST-Based Service Oriented Architecture for Dynamically Integrated Information Systems , 2007 .

[9]  Fakhri Alam Khan,et al.  Provenance based data integrity checking and verification in cloud environments , 2017, PloS one.

[10]  Suzanne W. Dietrich,et al.  Towards a hybrid relational and XML benchmark for loosely-coupled distributed data sources , 2015, J. Syst. Softw..

[11]  Steve Vinoski.  RESTful Web Services Development Checklist , 2008, IEEE Internet Computing.

[12]  Jun Sawamoto,et al.  Virtual Database Technology for Distributed Database in Ubiquitous Computing Environment , 2012 .

[13]  Craig Russell.  Bridging the Object-Relational Divide , 2008, ACM Queue.

[14]  Antonio Puliafito,et al.  Integration of CLEVER clouds with third party software systems through a REST web service interface , 2012, 2012 IEEE Symposium on Computers and Communications (ISCC).

[15]  Shiyong Lu,et al.  Efficient schema-based XML-to-Relational data mapping , 2007, Inf. Syst..

[16]  Saeed Karshenas,et al.  Integrating Distributed Sources of Information for Construction Cost Estimating using Semantic Web and Semantic Web Service technologies , 2015 .

[17]  Lijun Jiang,et al.  A Grid-Based Model for Integration of Distributed Medical Databases , 2009, Journal of Digital Imaging.

[18]  J. Wenny Rahayu,et al.  Semantic-based Structural and Content indexing for the efficient retrieval of queries over large XML data repositories , 2014, Future Gener. Comput. Syst..

[19]  Domenico Talia,et al.  A Service-Oriented System to Support Data Integration on Data Grids , 2007, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07).

[20]  Jun Sawamoto,et al.  Virtual Database Technology for Distributed Database , 2010, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.