Project Summary
Innovated mobile technologies offer interesting opportunities in many domains, such as health care, transportation, and commerce. They enable distant monitoring and permit consideration of parameters such as patient's and physician's mobility. This makes it possible to develop novel applications, such as mobile health services for telemedicine and assisted ambient living (particularly in rural areas) and mobile traffic services. Nevertheless, the amount of data to be generated and queried is very large and diverse collected from multiple sources. The combination of big data and mobility leads to a major challenge: how to efficiently process queries from a myriad of mobile devices on a large amount of data, especially when the data are to be stored in a novel data management system supplied by several cloud providers with possibly different pricing models? To solve this challenge, this project develops novel mobile cloud data management architectures and novel query processing algorithms that leverage mobile user's storage and computation power and take mobile user's mobility, disconnection, energy limitation, and cloud service provider's pricing models into consideration in order to improve query response time, while reducing the amount of money that must be paid to the cloud service providers. The research is evaluated using both real and synthetic datasets by means of prototyping.
The project makes important impacts not only on research but also on education as it provides training for graduate and undergraduate students in the areas of critical national needs: cloud and mobile database management systems, big data and high-end computing. The project is an international collaboration effort between the University of Oklahoma (OU) and Blaise Pascal University in France. Both universities participate in the design, prototype and evaluation of the architectures and algorithms as well as the education and outreach aspects of the project.