Dynamic power management of complex systems using Generalized Stochastic Petri Nets

Qinru Qiu, Qing Wu, Massoud Pedram

Research output: Chapter in Book/Report/Conference proceedingConference contribution

60 Scopus citations

Abstract

In this paper, we introduce a new technique for modeling and solving the dynamic power management (DPM) problem for systems with complex behavioral characteristics such as concurrency, synchronization, mutual exclusion and conflict. We model a power-managed distributed computing system as a controllable Generalized Stochastic Petri Net (GSPN) with cost. The obtained GSPN model is automatically converted to an equivalent continuous-time Markov decision process. Given the delay constraints, the optimal power management policy for system components as well as the optimal dispatch policy for requests are calculated by solving a linear programming problem based on the Markov decision process. Experimental results show that the proposed technique can achieve more than 20% power saving compared to other existing DPM techniques.

Original languageEnglish (US)
Title of host publicationProceedings - Design Automation Conference
PublisherIEEE Computer Society
Pages352-356
Number of pages5
StatePublished - 2000
Externally publishedYes
EventDAC 2000: 37th Design Automation Conference - Los Angeles, CA, USA
Duration: Jun 5 2000Jun 9 2000

Other

OtherDAC 2000: 37th Design Automation Conference
CityLos Angeles, CA, USA
Period6/5/006/9/00

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering

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