Medical Data Management in Clouds
Context:
High Performance Computing architectures aim at supporting the increasing needs of
both scientific and industrial applications. Among these architectures, cloud
computing, which has been used by major companies like Google, Microsoft and
Amazon, is of a particular interest. Cloud computing supplies high computing and
storage resources via several data centers. Thanks to the use of inexpensive,
commodity hardware and open source implementations, experimenting with these
techniques is relatively easy, even with a low budget. Cloud computing offers new
opportunities to achieve scalable and efficient database management systems to deal
with data volumes or structures that cannot be managed by classical relational or
object Data Base Management Systems.
The development of medical imagery technologies and the abolition of radiologic
movies have led to an explosion of the amount of numerical data stored by health care
organizations. In addition, legal constraints impose long-term storage of medical
exams. In current systems, the cost of an exam is mostly due to its storage, which is
about 75% of the total cost. That is why it is crucial to find a solution to improve the
warehousing of medical data. Such a solution includes the use of cloud computing.
Challenges:
This project aims at developing a medical data management system on clouds, based
on the DICOM standard, that is accessible from mobile devices. The main challenge
for such a system is to manage medical data with respect to properties of cloud
computing. As a consequence, the system must be user-friendly, both for the software
provider (leaving the maintenance aspects to the infrastructure’s supplier) and for the
end user (since physicians are not experts in computer science and particularly in
databases). The proposal will have to be elastic to propose a high level of quality of
service (especially for querying a large amount of data in clouds from mobile devices)
with regard to the pay-as-you go model to propose attractive pricing.
The projected schedule for this project is as follows:

considering use cases and studying the state of the art of the relevant research

proposing a conceptual medical data management system for clouds

developing a prototype for such a system to be validated by both developers
(for performance analysis) and end users (for accessibility evaluation).