Multiparadigm scheduling for distributed real-time embedded computing

  • Christopher D. Gill
  • , Ron K. Cytron
  • , Douglas C. Schmidt

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

Increasingly complex requirements, coupled with with tighter economic and organizational constraints, are making it hard to build complex distributed real-time embedded (ORE) systems entirely from scratch. Therefore, the proportion of DRE systems made up of commercial-off-the-shelf (COTS) hardware and software is increasing significantly. There are relatively few systematic empirical studies, however, that illustrate how suitable COTS-based hardware and software have become for mission-critical DRE systems. This paper provides the following contributions to the study of real-time quality-of-service (QoS) assurance and performance in COTS-based DRE systems: it presents evidence that flexible configuration of COTS middleware mechanisms, and the operating system (OS) settings they use, allows DRE systems to meet critical QoS requirements over a wider range of load and jitter conditions than statically configured systems; it shows that in addition to making critical QoS assurances, noncritical QoS performance can be improved through flexible support for alternative scheduling strategies; and it presents an empirical study of three canonical scheduling strategies; specifically the conditions that predict success of a strategy for a production-quality DRE avionics mission computing system. Our results show that applying a flexible scheduling framework to COTS hardware, OSs, and middleware improves real-time QoS assurance and performance for mission-critical DRE systems.

Original languageEnglish
Pages (from-to)183-197
Number of pages15
JournalProceedings of the IEEE
Volume91
Issue number1
DOIs
StatePublished - 2003

Keywords

  • Distributed real-time and embedded systems
  • Dynamic scheduling algorithms and analysis
  • Middleware and APIs
  • Mission-critical systems
  • Quality-of-service (QoS) issues

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