2KQ+: An Integrated Approach of QoS Compilation and Reconfigurable, Component-Based Run-Time Middleware for the Unified QoS Management Framework

  • Duangdao Wichadakul
  • Klara Nahrstedt
  • Xiaohui Gu
  • Dongyan Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2218)


Different distributed component-based applications (e.g., distributed multimedia, library information retrieval, secure stock trading applications), running in heterogeneous execution environments, need different quality of service (QoS). The semantics of QoS requirements and their provisions are application-specific, and they vary among different application domains. Furthermore, QoS provisions vary per applications in heterogeneous execution environments due to the varying distributed resource availability. Making these applications QoS-aware during the development phase, and ensuring their QoS guarantees during the execution phase is complex and hard

In this paper, we present a unified QoS management framework, called 2K Q+. This framework extends our existing run-time 2K Q middleware system [1] by including our uniform QoS programming environment and our automated QoS compilation system (Q-Compiler). The uniform QoS programming and its corresponding QoS compilation allow and assist the application developer to build different component-based domain applications in QoS-aware fashion. Furthermore, this novel programming and compilation environment enables the applications to be instantiated, managed, and controlled by the same reconfigurable, component-based run-time middleware, such as 2K Q , in heterogeneous environments. Our experimental results show that different QoS-aware applications, using the 2K Q+ > framework, get configured and setup fast and efficiently


Service Component Application Execution Resource Translation Information Retrieval Service Decoder Service 
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

© IFIP International Federation for Information Processing 2001

Authors and Affiliations

  • Duangdao Wichadakul
    • 1
  • Klara Nahrstedt
    • 1
  • Xiaohui Gu
    • 1
  • Dongyan Xu
    • 1
  1. 1.Department of Computer ScienceUniversity of IllinoisUrbana-Champaign

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