Feedback Control Scheduling in Distributed Real-Time Systems

  • Authors:

  • John A. Stankovic;Tian He;Tarek Abdelzaher;Mike Marley;Gang Tao;Sang Son;Cenyan Lu

  • Affiliations:

  • -;-;-;-;-;-;-

  • Venue:
  • RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
  • Year:
  • 2001

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Abstract

Distributed soft real-time systems are becoming increasinglyunpredictable due to several important factors such as theincreasing use of commercial-off-the-shelf components, the trend towards open systems, and the proliferation of data-drivenapplications whose execution parameters vary significantly with input data.Such systems are less amenable to traditional worst-case real-time analysis.Instead, system-wide feedback control is needed to meet performance requirements.In this paper, we ex-tend our previous work on developing software control algorithms based on a theory of feedback control to distributed systems.Our approach makes three importantcontributions.First, it allows the designer for a distributedreal-time application to specify the desired temporalbehavior of system adaptation, such as the speed of convergence to desired performance upon load or resourcechanges.This is in contrast to specifying only steady statemetrics, e.g., deadline miss ratio.Second, unlike QoS optimization approaches, our solution meets performanceguarantees without accurate knowledge of task executionparameters - a key advantage in an unpredictable environment.Third, in contrast to ad hoc algorithms based on intuitionand testing, our solution has a basis in the theoryand practice of feedback control scheduling. Performanceevaluation reveals that the solution not only has excellentsteady state behavior, but also meets stability, overshoot,and settling time requirements.We also show that the solution outperforms several other algorithms available inthe literature.