Joint Sleep Scheduling and Mode Assignment in Wireless Cyber-Physical Systems

  • Authors:
  • Chun Jason Xue;Guoliang Xing;Zhaohui Yuan;Zili Shao;Edwin Sha

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • ICDCSW '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems Workshops
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recent years have witnessed the deployment of wireless Cyber-Physical Systems(CPS) for a variety of important applications.A key requirement for wireless CPS systems is to sustain a long lifetime on limited power supplies. At the same time, due to the criticality of CPS applications, many computation and communication tasks must be finished within timing constraints to avoid undesirable or even catastrophic consequences.%%Minimizing network-wide energy consumption is a key issue in designing%cyber-physical systems.While a lot of work has been done to manage energy consumption on single processor real-time systems,little work has been done in network-wide energy consumption management for real-time applications.Existing work on network-wide energy minimization assumes that the underlying network is always connected, which is not consistent with the practice in which wireless nodes often turn off their network interfaces in a sleep schedule to reduce energy consumption.%Moreover, existing sleep scheduling techniques are unaware of computation status and often%lead to unnecessary wakeup overhead.%In this paper, we propose solutions to minimize%network-wide energy consumption for real-time tasks with precedence%constraints executing on wireless cyber-physical systems.This paper jointly considers the radio sleep scheduling of wireless nodes and the execution modes of processors. Based on wireless network topologies, different schemes are proposed to minimize energy consumption while guaranteeing the timing and precedence constraints. When the precedence graph is a tree, optimal result on energy management is achieved. The experiments show that our approach significantly reduces total energy consumption compared with the previous work.