Collaborative User Services for Private Data Management (CUSP)


Project Leader: Dr. D. Jutla


The CUSP (Collaborative User Services for Private Data Management) project intends to deliver sophisticated user privacy services over the Semantic Web. This Canadian project is a collaborative effort between faculty in the Sobey School of Business, SMU, and the Faculty of Computer Science, Dalhousie University.


Currently many knowledge-intensive privacy-related tasks are manual. Using Semantic Web technologies (OWL, RDF, XML, UDDI, SOAP, and WSDL), knowledge-base and database methodologies, and building on the P3P platform (XML vocabulary for privacy), the CUSP project automates human decision making processes with respect to online privacy.


To date, the project has delivered peer-reviewed client and Web-side architectures and implementation strategies to support the creation of novel and sophisticated Privacy Web services. Specifically, it has proposed novel Web services for a 3-way comparison of user preferences, business privacy policies, and government and industrial regulations and standards. It also extends work of the P3P W3C Group.


We are in the process of disseminating further research results, as well as continuing further project work. We invite researchers and students in the natural language, user interface, and user studies areas to work with us to evaluate further design and implementation strategies. There are many opportunities for software engineering students, as well as students interested in trust and globalization issues for e-business, on this project.




Interoperable Caching in Middleware and Web Environments:
QoS Framework and Methods


In collaboration with Dr. D. Jutla.


E-business is supported by numerous systems in which middleware plays an important role while caching is one of the fundamental techniques to improve the response time of systems.


Numerous caching algorithms have been proposed, studied, and implemented in support of transactional and non-transactional caching. We are examining techniques that enable interoperability of different transactional caching algorithms so that they could co-exist within the same environment.


We are studying models for middleware components that would enable us to predict their consumption of infrastructural resources and delays and hence to enable allocation of resources and balance the workload. We are examining adaptation of caching techniques in Distributed DBs (DDBs) to the environment of middleware components supporting web-based applications. To ensure that the middleware provides appropriate services to appropriate clients, we have developed a Quality of Services (QoS) framework, and a supporting tool-kit, for monitoring of middleware and its infrastructure in which it operates.