The application is able to serve many concurrent user at a time. To ensure sufficient computational resources without extensive investments into hardware we developed a framework for construction of distributed computational environments using a large number of common personal computers connected to the internet (workers). Here we present the idea using 3 OpenShift geras: 1 gear serves the task server and 2 gers power worker nodes.
The framework is based on the client-server architecture, see the Figure. It core components are:
Since workers communicate over http protocol, they can run without any special need of configuring firewalls etc. This design offers a good scalability and almost seamless extension of computational resources. In the case of a large number of concurrent users, e.g. a group of students in a class, the number of workers can be easily increased just by launching the worker code on computers with Linux, OS X or Windows operating systems connected to the internet. As a side effect we obtain a robust solution where the functionality of the system is not influenced by unavailability or a failure of a subset of workers.
When the task is done, we can view results by clicking Task details from the drop-down menu activated by pressing . Table with comprehensive review of task. Thera are three tabs:
After selecting Show on map from drop-down menu a modal window with vizualization of selected radiological quantity appears: