Using JIT Compilation and Configurable Runtime Systems for Efficient Deployment of Java Programs on Ubiquitous Devices

  • Radu Teodorescu
  • Raju Pandey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2201)


As the proliferation of ubiquitous devices moves computation away from the conventional desktop computer boundaries, distributed systems design is being exposed to new challenges. A distributed system supporting a ubiquitous computing application must deal with a wider spectrum of hardware architectures featuring structural and functional differences, and resources limitations. Due to its architecture independent infrastructure and object-oriented programming model, the Java programming environment can support flexible solutions for addressing the diversity among these devices. Unfortunately, Java solutions are often associated with high costs in terms of resource consumption, which limits the range of devices that can benefit from this approach. In this paper, we present an architecture that deals with the cost and complexity of running Java programs by partitioning the process of Java program execution between system nodes and remote devices. The system nodes prepare a Java application for execution on a remote device by generating device-specific native code and application-specific runtime system on the fly. The resulting infrastructure provides the flexibility of a high-level programming model and the architecture independence specific to Java. At the same time the amount of resources consumed by an application on the targeted device are comparable to that of a native implementation.


Mobile Agent Ubiquitous Computing Runtime System Embed Device Method Invocation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Radu Teodorescu
    • 1
  • Raju Pandey
    • 1
  1. 1.Parallel and Distributed Computing Laboratory Computer Science DepartmentUniversity of CaliforniaDavis

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