Decision-driven scheduling

Jung Eun Kim, Tarek Abdelzaher, Lui Sha, Amotz Bar-Noy, Reginald L. Hobbs, William Dron

Research output: Contribution to journalArticlepeer-review


This paper presents a scheduling model, called decision-driven scheduling, elaborates key optimality results for a fundamental scheduling model, and evaluates new heuristics solving more general versions of the problem. In the context of applications that need control and actuation, the traditional execution model has often been either time-driven or event-driven. In time-driven applications, sensors are sampled periodically, leading to the classical periodic task model. In event-driven applications, sensors are sampled when an event of interest occurs, such as motion-activated cameras, leading to an event-driven task activation model. In contrast, in decision-driven applications, sensors are sampled when a particular decision must be made. We offer a justification for why decision-driven scheduling might be of increasing interest to Internet-of-things applications, and explain why it leads to interesting new scheduling problems (unlike time-driven and event-driven scheduling), including the problems addressed in this paper.

Original languageEnglish (US)
Pages (from-to)514-551
Number of pages38
JournalReal-Time Systems
Issue number3
StatePublished - Jul 15 2019


  • Decision-driven
  • Disaster response infrastructure
  • Freshness
  • Internet of Things
  • Smart cities

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Computer Science Applications
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering


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