Resource-Centric Real-Time Kernel and Middleware Services

Abstract

This report provides an in depth look at the problem of OS resource management for real-time and multimedia systems where multiple activities with different timing constraints must be scheduled concurrently. Time on a particular resource is shared among its users and must be globally managed in real-time and multimedia systems. A resource kernel is meant for use in such systems and is defined to be one that provides timely, guaranteed and protected access to system resources. The resource kernel allows applications to specify only their resource demands leaving the kernel to satisfy those demands using hidden resource management schemes. This separation of resource specification from resource management allows OS-subsystem-specific customization by extending, optimizing, or even replacing resource management schemes. As a result, this resource-centric approach can be implemented with any of several different resource management schemes. Since the same application may consume a different amount of time on different platforms, the resource kernel must allow such resource consumption times to be portable across platforms, and to be automatically calibrated. Our resource management scheme is based on resource reservation and satisfies these goals.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2002
Accession Number
ADA408745

Entities

People

  • Raj Rajkumar

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Application Software
  • Computer Programming
  • Computers
  • Control Systems
  • Java Programming Language
  • Multimedia
  • Operating Systems
  • Packet Loss
  • Platforms
  • Reliability
  • Resource Management
  • Specifications
  • Standards
  • Test And Evaluation
  • Throughput

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Parallel and Distributed Computing.