Lifetime aware resource management for sensor network using distributed genetic algorithm

Qiu Qinru; Wu Qing; Daniel Burns; Douglas Holzhauer

doi:10.1145/1165573.1165618

Lifetime aware resource management for sensor network using distributed genetic algorithm

Qiu Qinru, Wu Qing, Daniel Burns, Douglas Holzhauer

Research output: Chapter in Book/Entry/Poem › Conference contribution

17 Scopus citations

Abstract

In this work we consider lifetime-aware resource management for sensor network using distributed genetic algorithm (GA). Our goal is to allocate different detection methods to different sensor nodes in the way such that the required detection probability can be achieved while the network lifetime is maximized. The contribution of this paper is twofold. Firstly, the resource management problem is formulated as a constraint optimization problem and is solved using a distributed GA. Secondly, empirical analysis results are provided that reveals the relationship between the configuration parameters and the quality of the search. A regression model is designed to estimate the runtime of the distributed GA given the configuration parameters. The model is utilized to find energy efficient configurations of the algorithm.

Original language	English (US)
Title of host publication	ISLPED'06 - Proceedings of the 2006 International Symposium on Low Power Electronics and Design
Pages	191-196
Number of pages	6
DOIs	https://doi.org/10.1145/1165573.1165618
State	Published - 2006
Externally published	Yes
Event	ISLPED'06 - 11th ACM/IEEE International Symposium on Low Power Electronics and Design - Tegernsee, Bavaria, Germany Duration: Oct 4 2006 → Oct 6 2006

Publication series

Name	Proceedings of the International Symposium on Low Power Electronics and Design
Volume	2006
ISSN (Print)	1533-4678

Other

Other	ISLPED'06 - 11th ACM/IEEE International Symposium on Low Power Electronics and Design
Country/Territory	Germany
City	Tegernsee, Bavaria
Period	10/4/06 → 10/6/06

Keywords

Distributed genetic algorithm
Energy aware design
Resource management
Sensor network

ASJC Scopus subject areas

General Engineering

Access to Document

10.1145/1165573.1165618

Cite this

Qinru, Q., Qing, W., Burns, D., & Holzhauer, D. (2006). Lifetime aware resource management for sensor network using distributed genetic algorithm. In ISLPED'06 - Proceedings of the 2006 International Symposium on Low Power Electronics and Design (pp. 191-196). (Proceedings of the International Symposium on Low Power Electronics and Design; Vol. 2006). https://doi.org/10.1145/1165573.1165618

Lifetime aware resource management for sensor network using distributed genetic algorithm. / Qinru, Qiu; Qing, Wu; Burns, Daniel et al.
ISLPED'06 - Proceedings of the 2006 International Symposium on Low Power Electronics and Design. 2006. p. 191-196 (Proceedings of the International Symposium on Low Power Electronics and Design; Vol. 2006).

Research output: Chapter in Book/Entry/Poem › Conference contribution

Qinru, Q, Qing, W, Burns, D & Holzhauer, D 2006, Lifetime aware resource management for sensor network using distributed genetic algorithm. in ISLPED'06 - Proceedings of the 2006 International Symposium on Low Power Electronics and Design. Proceedings of the International Symposium on Low Power Electronics and Design, vol. 2006, pp. 191-196, ISLPED'06 - 11th ACM/IEEE International Symposium on Low Power Electronics and Design, Tegernsee, Bavaria, Germany, 10/4/06. https://doi.org/10.1145/1165573.1165618

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abstract = "In this work we consider lifetime-aware resource management for sensor network using distributed genetic algorithm (GA). Our goal is to allocate different detection methods to different sensor nodes in the way such that the required detection probability can be achieved while the network lifetime is maximized. The contribution of this paper is twofold. Firstly, the resource management problem is formulated as a constraint optimization problem and is solved using a distributed GA. Secondly, empirical analysis results are provided that reveals the relationship between the configuration parameters and the quality of the search. A regression model is designed to estimate the runtime of the distributed GA given the configuration parameters. The model is utilized to find energy efficient configurations of the algorithm.",

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AU - Qing, Wu

AU - Burns, Daniel

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AB - In this work we consider lifetime-aware resource management for sensor network using distributed genetic algorithm (GA). Our goal is to allocate different detection methods to different sensor nodes in the way such that the required detection probability can be achieved while the network lifetime is maximized. The contribution of this paper is twofold. Firstly, the resource management problem is formulated as a constraint optimization problem and is solved using a distributed GA. Secondly, empirical analysis results are provided that reveals the relationship between the configuration parameters and the quality of the search. A regression model is designed to estimate the runtime of the distributed GA given the configuration parameters. The model is utilized to find energy efficient configurations of the algorithm.

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KW - Sensor network

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Lifetime aware resource management for sensor network using distributed genetic algorithm

Abstract

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Keywords

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