Hierarchical control of multiple resources in distributed real-time and embedded systems

  • Authors:

  • Nishanth Shankaran;Xenofon D. Koutsoukos;Douglas C. Schmidt;Yuan Xue;Chenyang Lu

  • Affiliations:

  • Department of Electrical Engineering and Computer Science, Institute for Software Integrated Systems (ISIS), Vanderbilt University, Nashville, USA 37203;Department of Electrical Engineering and Computer Science, Institute for Software Integrated Systems (ISIS), Vanderbilt University, Nashville, USA 37203;Department of Electrical Engineering and Computer Science, Institute for Software Integrated Systems (ISIS), Vanderbilt University, Nashville, USA 37203;Department of Electrical Engineering and Computer Science, Institute for Software Integrated Systems (ISIS), Vanderbilt University, Nashville, USA 37203;Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, USA 63130-4899

  • Venue:
  • Real-Time Systems
  • Year:
  • 2008

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Abstract

Real-time and embedded systems have traditionally been designed for closed environments where operating conditions, input workloads, and resource availability are known a priori, and are subject to little or no change at runtime. There is increasing demand, however, for adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational conditions, input workload, and resource availability cannot be characterized accurately a priori. A challenging problem faced by researchers and developers of such systems is devising effective adaptive resource management strategies that can meet end-to-end quality of service (QoS) requirements of applications. To address key resource management challenges of open DRE systems, this paper presents the Hierarchical Distributed Resource-management Architecture (HiDRA), which provides adaptive resource management using control techniques that adapt to workload fluctuations and resource availability for both bandwidth and processor utilization simultaneously.This paper presents three contributions to research in adaptive resource management for DRE systems. First, we describe the structure and functionality of HiDRA. Second, we present an analytical model of HiDRA that formalizes its control-theoretic behavior and presents analytical assurance of system performance. Third, we evaluate the performance of HiDRA via experiments on a representative DRE system that performs real-time distributed target tracking. Our analytical and empirical results indicate that HiDRA yields predictable, stable, and efficient system performance, even in the face of changing workload and resource availability.