A data access framework for service-oriented rich clients

  • Authors:

  • Qi Zhao;Xuanzhe Liu;Xingrun Chen;Jiyu Huang;Gang Huang;Hong Mei

  • Affiliations:

  • Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871

  • Venue:
  • Service Oriented Computing and Applications
  • Year:
  • 2012

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Abstract

Facilitated by the SOA and new Web technologies, Service-Oriented Rich Clients (SORCs) compose various Web-delivered services in Web browser to create new applications. The SORCs support client-side data storage and manipulation and provide more features than traditional thin clients. However, the SORCs might suffer from data access issues, mainly due to both client-side incompatible data sources and server-side improper or even undesirable cache strategies. Addressing the data access issues, this paper proposes a data access framework for SORCs. The main contributions of this paper are as follows. First, the framework makes the SORCs accommodate heterogeneous local storage solutions and diverse Web browsers properly. The framework abstracts the underlying details of different local storages and selects the most proper data sources for current SORC in use. Secondly, the framework provides a cache mechanism, which supports client-side customized cache strategies. An adaptive technique for the strategies is also proposed to adjust cache strategies based on users' historical actions to achieve better performance.