Reducing energy consumption with batched task executions

Kenichi Yasukata; Tetsuro Horikawa; Michio Honda; Hideyuki Tokuda

doi:10.1145/2426656.2426699

Reducing energy consumption with batched task executions

Kenichi Yasukata
, Tetsuro Horikawa
, Michio Honda
, Hideyuki Tokuda

Faculty of Environment and Information Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems
Pages	343-344
Number of pages	2
DOIs	https://doi.org/10.1145/2426656.2426699
Publication status	Published - 2012
Event	10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012 - Toronto, ON, Canada Duration: 2012 Nov 6 → 2012 Nov 9

Publication series

Name	SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems

Other

Other	10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012
Country/Territory	Canada
City	Toronto, ON
Period	12/11/6 → 12/11/9

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Operating system
Real-time and embedded systems

ASJC Scopus subject areas

Computer Networks and Communications

Access to Document

10.1145/2426656.2426699

Cite this

Reducing energy consumption with batched task executions. / Yasukata, Kenichi; Horikawa, Tetsuro; Honda, Michio et al.
SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems. 2012. p. 343-344 (SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yasukata, K, Horikawa, T, Honda, M & Tokuda, H 2012, Reducing energy consumption with batched task executions. in SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems. SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems, pp. 343-344, 10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012, Toronto, ON, Canada, 12/11/6. https://doi.org/10.1145/2426656.2426699

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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.",

keywords = "Operating system, Real-time and embedded systems",

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AB - 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.

KW - Operating system

KW - Real-time and embedded systems

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AN - SCOPUS:84873425708

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BT - SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems

T2 - 10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012

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ER -

Reducing energy consumption with batched task executions

Abstract

Publication series

Other

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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