Reducing Energy Consumption with Batched Task Executions

Kenichi Yasukata, Tetsuro Horikawa, Michio Honda, Hideyuki Tokuda

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

Abstract

In sensing systems, data compression is a promised way to save energy because it reduces the rate of data transmission, but less attention has been paid to the underlying task scheduling algorithms. We present a Double Rate Bundle Scheduling algorithm (DRBS) that maximizes the sleep state period of the CPU to reduce energy consumption. Our prototype implementation in a Mote device improves energy efficiency up to 8% compared to existing algorithms.
Original languageEnglish
Title of host publicationProceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Place of PublicationNew York, NY, USA
PublisherACM Association for Computing Machinery
Pages343–344
Number of pages2
ISBN (Print)9781450311694
DOIs
Publication statusPublished - 6 Nov 2012
Event10th ACM Conference on Embedded Network Sensor Systems - Toronto, Canada
Duration: 6 Nov 20129 Nov 2012
Conference number: 10

Conference

Conference10th ACM Conference on Embedded Network Sensor Systems
Abbreviated titleSenSys '12
CountryCanada
CityToronto
Period6/11/129/11/12

Keywords

  • real-time and embedded systems
  • operating system

Fingerprint

Dive into the research topics of 'Reducing Energy Consumption with Batched Task Executions'. Together they form a unique fingerprint.

Cite this