Big Data Management System for Biomedical Images to Improve Short-term and Long-term Storage

In digital pathology, an electronic system in the biomedical domain storage of the files is a big constrain and because all the analysis and annotation takes place at every user-end manually, it becomes even harder to manage the data that is being shared inside an enterprise. Therefore, we need such a storage system which is not only big enough to store all the data but also manage it and making communication of that data much easier without losing its true from. A virtual server setup is one of those techniques which can solve this issue. We set a main server which is the main storage for all the virtual machines(that are being used at user-end) and that main server is controlled through a hypervisor so that if we want to make changes in storage overall or the main server in itself, it could be reached remotely from anywhere by just using the server's IP address. The server in our case includes XML-RPC based API which are transmitted between computers using HTTP protocol. JAVA API connects to HTTP/HTTPS protocol through JAVA Runtime Environment and exists on top of other SDK web services for the productivity boost of the running application. To manage the server easily, we use Tkinter library to develop the GUI and pmw magawidgets library which is also utilized through Tkinter. For managing, monitoring and performing operations on virtual machines, we use Python binding to XML-RPC based API. After all these settings, we approach to make the system user friendly by making GUI of the main server. Using that GUI, user can perform administrative functions like restart, suspend or resume a virtual machine. They can also logon to the slave host of the pool in case of emergency and if needed, they can also filter virtual machine by the host. Network monitoring can be performed on multiple virtual machines at same time in order to detect any loss of network connectivity.