In the traditional development model, every author of a multimedia stream analysis application has at his disposal only some basic tools and libraries available in distributed processing systems (e.g. MPI). With these tools he has to single-handedly implement the whole set of necessary functionality, which takes a lot of effort.

The new model introduced in KASKADA platform allows for a significant reduction of the programmers' efforts through providing them with a whole spectrum of functions used in multimedia processing. Operations such as effective data transmission, support of popular multimedia codecs and monitoring of service execution are carried out automatically, which substantially reduces the complexity of the application's architecture.

The improved processing model additionally considers the possibility of using already existing services, stored in the KASKADA platform's repository. Creating new data analysis scenarios with ready-to-use, thoroughly tested components allows for a significant reduction of time necessary for deployment of new applications.

User Console is used for creation, management and execution of services. Simple and complex services can be created by developers through a web interface. It is also responsible for management and supervision of the computing nodes and shows information about the state of individual nodes, received from the Monitor.

The Platform uses a task scheduler to assign tasks to computing nodes. This concerns both data processing services and tasks launched on the multimedia stream management server. The scheduler allows for effective utilisation of the available resources and increases reliability of the whole Platform.

The successful detection of specified situations causes generation of an event which is passed to the Event Management component. Each event is stored for administrative and safety purposes and could be delivered to the external recipients through e-mail or JMS queue.

Business integration

Functionality implemented in KASKADA platform allows for broad integration with business and public units. Through negotiating appropriate contracts by intermediate agencies, applications can be used by emergency services such as medical emergency or fire services.

Quality analysis

One of the basic aims of KASKADA platform development was to assure high quality of provided services. Through utilising the computing power of the Galera supercomputer, as well as using advanced resource allocation algorithms and efficient data stream processing techniques, high scalability of the platform was ensured, which allows for execution of a large number of simultaneously working services. Additionally, specific features of parallel real-time data processing were taken into consideration, so that the services running in KASKADA platform are characterised by low data loss, which corresponds to high quality of the obtained results.

KASKADA team is a close-knit group of nine passionate individuals from Gdańsk University of Technology who are enthusiastic about high performance computing and multimedia processing. In our team we have one PhD., six MSc. Eng. (including five PhD. students) and two Eng. We specialize in C++ (e.g. RDMA, MPI, Boost and GStreamer) and Java technologies such as Spring, Hibernate and ActiveMQ. Our developers have rich experience in scientific and business projects, such as Beesy Cluster, Tempus, Copernicus or Endoscopy Recommender System (ERS). Part of our team have certifications from IBM, Oracle/Sun, Novell and LPI (e.g. OCPJP and LPIC). We focus not only on development, but we also do research that is connected with HPC. We create models based on diagnostic data, we design and execute validation tests to prove them, and we use them to solve real-life problems. We have published more than 15 publications in national and international journals and conferences.

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  Barłomiej Daca

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  Adam Glinianowicz

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  Rafał Knopa

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  Michał Nykiel

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  Piotr Orzechowski

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  Piotr Sawicki

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  Karol Zalewski

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  Tomasz Ziółkowski