Power-efficient scheduling for heterogeneous distributed real-time embedded systems

Jiong Luo, Niraj K. Jha

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


This paper addresses the problem of variable-voltage scheduling of multirate periodic task graphs (i.e., tasks with precedence relationships) in heterogeneous distributed real-time embedded systems. Such an embedded system may contain general-purpose processors, field-programmable gate arrays, and application-specific integrated circuits. First, we discuss the implications of the distribution of power consumption, i.e., power profile, of tasks and characteristics of voltage-scalable processing elements (PEs) on variable-voltage scaling. Then, we present a power-efficient variable-voltage scheduling algorithm to address these implications. The scheduling algorithm performs execution order optimization of scheduled events to increase the chances of scaling down voltages and frequencies of these voltage-scalable PEs in the distributed embedded system. It also performs power-profile and timing-constraint driven slack allocation to maximize power reduction via voltage scaling, based on the observation that the energy consumption of a task on a voltage-scalable PE is normally a convex function of the clock speed. The scheduling algorithm is also effective in the case where the variations in power consumption of different tasks can be ignored. It can be included in the inner loop of a system-level synthesis tool for design space exploration of real-time heterogeneous embedded systems, since it is very fast. We show its efficacy by comparing it to other approaches from the literature.

Original languageEnglish (US)
Pages (from-to)1161-1170
Number of pages10
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Issue number6
StatePublished - Jun 2007

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


  • Distributed systems
  • Low power
  • Scheduling
  • Voltage scaling


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