Doc. Dr. Ing. Otto Fučík
|Czech title:||Java platform for hIgh PErformance and Real-time large scale data management (JUNIPER)|
|Research leader:||Smrž Pavel|
|Team leaders:||Rychlý Marek, Škoda Petr|
|Team members:||Dytrych Jaroslav, Fučík Otto, Jeřábek Jan (), Kouřil Jan, Musil Petr, Otrusina Lubomír, Zachariáš Michal|
|Agency:||Information and Communication Technologies (ICT) 7th Framework programme - Seventh Research Framework Programme|
|Keywords:||Performance guarantees, realtime, Big Data, streaming
data, stored data, parallelisation, Java|
|The efficient and real-time exploitation of large streaming data sources and stored data poses many questions
regarding the underlying platform, including:
1) Performance - how can the potential performance of the platform be exploited effectively by arbitrary
2) Guarantees - how can the platform support guarantees regarding processing streaming data sources and
accessing stored data; and
3) Scalability - how can scalable platforms and applications be built.
The fundamental challenge addressed by the project is to enable application development using an industrial
strength programming language that enables the necessary performance and performance guarantees required
for real-time exploitation of large streaming data sources and stored data.
The project's vision is to create a Java Platform that can support a range of high-performance Intelligent
Information Management application domains that seek real-time processing of streaming data, or real-time
access to stored data. This will be achieved by developing Java and UML modelling technologies to provide:
1) Architectural Patterns - using predefined libraries and annotation technology to extend Java with new
directives for exploiting streaming I/O and parallelism on high performance platforms;
2) Virtual Machine Extensions - using class libraries to extend the JVM for scalable platforms;
3) Java Acceleration - performance optimisation is achieved using Java JIT to Hardware (FPGA), especially to
enable real-time processing of fast streaming data;
4) Performance Guarantees - will be provided for common application real-time requirements; and
5) Modelling - of persistence and real-time within UML / MARTE to enable effective development, code
generation and capture of real-time system properties.
The project will use financial and web streaming case studies from industrial partners to provide industrial data
and data volumes, and to evaluate the developed technologies.