Proactive power optimization of sensor networks

Rahul Khanna; Huaping Liu; Hsiao-Hwa Chen

doi:10.1109/ICC.2008.406

Proactive power optimization of sensor networks

Rahul Khanna, Huaping Liu, Hsiao-Hwa Chen

Department of Engineering Science

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

2 Citations (Scopus)

Abstract

We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor power states and transmission power. The dynamic power scaling in conjunction with genetic algorithm jointly optimizes power states and topologies by dynamically monitoring workloads, packet arrivals, utilization data and quality-of-service compliance. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives.

Original language	English
Title of host publication	ICC 2008 - IEEE International Conference on Communications, Proceedings
Pages	2119-2123
Number of pages	5
DOIs	https://doi.org/10.1109/ICC.2008.406
Publication status	Published - 2008 Sept 12
Event	IEEE International Conference on Communications, ICC 2008 - Beijing, China Duration: 2008 May 19 → 2008 May 23

Publication series

Name	IEEE International Conference on Communications
ISSN (Print)	0536-1486

Other

Other	IEEE International Conference on Communications, ICC 2008
Country/Territory	China
City	Beijing
Period	08-05-19 → 08-05-23

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Electrical and Electronic Engineering

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10.1109/ICC.2008.406

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title = "Proactive power optimization of sensor networks",

abstract = "We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor power states and transmission power. The dynamic power scaling in conjunction with genetic algorithm jointly optimizes power states and topologies by dynamically monitoring workloads, packet arrivals, utilization data and quality-of-service compliance. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives.",

author = "Rahul Khanna and Huaping Liu and Hsiao-Hwa Chen",

year = "2008",

month = sep,

day = "12",

doi = "10.1109/ICC.2008.406",

language = "English",

isbn = "9781424420742",

series = "IEEE International Conference on Communications",

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booktitle = "ICC 2008 - IEEE International Conference on Communications, Proceedings",

note = "IEEE International Conference on Communications, ICC 2008 ; Conference date: 19-05-2008 Through 23-05-2008",

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T1 - Proactive power optimization of sensor networks

AU - Khanna, Rahul

AU - Liu, Huaping

AU - Chen, Hsiao-Hwa

PY - 2008/9/12

Y1 - 2008/9/12

N2 - We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor power states and transmission power. The dynamic power scaling in conjunction with genetic algorithm jointly optimizes power states and topologies by dynamically monitoring workloads, packet arrivals, utilization data and quality-of-service compliance. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives.

AB - We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor power states and transmission power. The dynamic power scaling in conjunction with genetic algorithm jointly optimizes power states and topologies by dynamically monitoring workloads, packet arrivals, utilization data and quality-of-service compliance. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives.

UR - http://www.scopus.com/inward/record.url?scp=51249102576&partnerID=8YFLogxK

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U2 - 10.1109/ICC.2008.406

DO - 10.1109/ICC.2008.406

M3 - Conference contribution

AN - SCOPUS:51249102576

SN - 9781424420742

T3 - IEEE International Conference on Communications

SP - 2119

EP - 2123

BT - ICC 2008 - IEEE International Conference on Communications, Proceedings

T2 - IEEE International Conference on Communications, ICC 2008

Y2 - 19 May 2008 through 23 May 2008

ER -

Proactive power optimization of sensor networks

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