(In-Development) Prototype for a MOCCAD Cache implementation on Android developed with Java
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.
- Implement Normalized Weighted Sum Algorithm into the prototype cache
- Multiple attribute selection
Jonathan Mullen
Mikaël Perrin
Florian Helff
Chenxiao Wang
Jason Arenson
Zachary Arani
Christoph Kinzel
Richard Collet
Farah Kouiss
Maxime P Merrien
This material is based upon work supported by the National Science Foundation under Grant No.1349285. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).