JUNIPER · Java platform for high-performance and real-time large scale data management

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 applications;2) Guarantees - how can the platform support guarantees regarding processing streaming data sources and accessing stored data; and3) Scalability - how can scalable platforms and applications be built.<br/>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.<br/>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; and5) Modelling - of persistence and real-time within UML / MARTE to enable effective development, code generation and capture of real-time system properties.<br/>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.