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Article

Optimizing sensor movement planning for energy efficiency

Authors:

Mary Jane Irwin,

Tom La PortaAuthors Info & Claims

ISLPED '05: Proceedings of the 2005 international symposium on Low power electronics and design

Pages 215 - 220

https://doi.org/10.1145/1077603.1077656

Published: 08 August 2005 Publication History

Abstract

Conserving the energy for motion is an important yet not-well-addressed problem in mobile sensor networks. In this paper, we study the problem of optimizing sensor movement for energy efficiency. We adopt a complete energy model to characterize the entire energy consumption in movement. Based on the model, we propose an optimal velocity schedule for minimizing energy consumption when the road condition is uniform; and a near optimal velocity schedule for the variable road condition by using continuous-state dynamic programming. Considering the variety in motion hardware, we also design one velocity schedule for simple microcontrollers, and one velocity schedule for relatively complex microcontrollers, respectively. Simulation results show that our velocity planning may have significant impact on energy conservation

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Cited By

Góra KGranosik GCybulski B(2024)Energy Utilization Prediction Techniques for Heterogeneous Mobile Robots: A ReviewEnergies10.3390/en1713325617:13(3256)Online publication date: 2-Jul-2024
https://doi.org/10.3390/en17133256
Gürgöze GTürkoğlu İ(2022)A Novel, Energy-Efficient Smart Speed Adaptation Based on the Gini Coefficient in Autonomous Mobile RobotsElectronics10.3390/electronics1119298211:19(2982)Online publication date: 20-Sep-2022
https://doi.org/10.3390/electronics11192982
Strebe LLee K(2022)Using Optimal Control Theory to Improve Path Planning For Battery Energy Maximization of an Unmanned Ground VehicleJournal of Machine Intelligence and Data Science10.11159/jmids.2022.004Online publication date: 2022
https://doi.org/10.11159/jmids.2022.004
Show More Cited By

Index Terms

Optimizing sensor movement planning for energy efficiency
1. General and reference
  1. Cross-computing tools and techniques
    1. Design

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Published In

cover image ACM Conferences

ISLPED '05: Proceedings of the 2005 international symposium on Low power electronics and design

August 2005

400 pages

ISBN:1595931376

DOI:10.1145/1077603

General Chairs:
Kaushik Roy
Purdue University
,
Vivek Tiwari
Intel

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 08 August 2005

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ISLPED05

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ISLPED05: International Symposium on Low Power Electronics and Design

August 8 - 10, 2005

CA, San Diego, USA

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Overall Acceptance Rate 398 of 1,159 submissions, 34%

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Cited By

Góra KGranosik GCybulski B(2024)Energy Utilization Prediction Techniques for Heterogeneous Mobile Robots: A ReviewEnergies10.3390/en1713325617:13(3256)Online publication date: 2-Jul-2024
https://doi.org/10.3390/en17133256
Gürgöze GTürkoğlu İ(2022)A Novel, Energy-Efficient Smart Speed Adaptation Based on the Gini Coefficient in Autonomous Mobile RobotsElectronics10.3390/electronics1119298211:19(2982)Online publication date: 20-Sep-2022
https://doi.org/10.3390/electronics11192982
Strebe LLee K(2022)Using Optimal Control Theory to Improve Path Planning For Battery Energy Maximization of an Unmanned Ground VehicleJournal of Machine Intelligence and Data Science10.11159/jmids.2022.004Online publication date: 2022
https://doi.org/10.11159/jmids.2022.004
Karimi-Bidhendi SGuo JJafarkhani H(2022)Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2021.313538521:7(4973-4988)Online publication date: Jul-2022
https://doi.org/10.1109/TWC.2021.3135385
Guo JJafarkhani H(2019)Movement-Efficient Sensor Deployment in Wireless Sensor Networks With Limited Communication RangeIEEE Transactions on Wireless Communications10.1109/TWC.2019.291419918:7(3469-3484)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1109/TWC.2019.2914199
Wang SXia MWu Y(2019)Backscatter Data Collection With Unmanned Ground Vehicle: Mobility Management and Power AllocationIEEE Transactions on Wireless Communications10.1109/TWC.2019.290255718:4(2314-2328)Online publication date: Apr-2019
https://doi.org/10.1109/TWC.2019.2902557
Santoshi G(2019)Mobile sensor nodes scheduling for bounded region coverageWireless Networks10.1007/s11276-018-1804-225:4(2157-2171)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1007/s11276-018-1804-2
Guo JJafarkhani H(2018)Movement-Efficient Sensor Deployment in Wireless Sensor Networks2018 IEEE International Conference on Communications (ICC)10.1109/ICC.2018.8422124(1-6)Online publication date: May-2018
https://doi.org/10.1109/ICC.2018.8422124
Jagtap AGomathi N(2018)Minimizing movement for network connectivity in mobile sensor networks: an adaptive approachCluster Computing10.1007/s10586-017-1660-3Online publication date: 23-Jan-2018
https://doi.org/10.1007/s10586-017-1660-3
Some RSamanta TBanerjee I(2017)Energy Aware Cluster Head Load Balancing Scheme for Heterogeneous Wireless Ad Hoc NetworkProceedings of the 18th International Conference on Distributed Computing and Networking10.1145/3007748.3018287(1-9)Online publication date: 5-Jan-2017
https://dl.acm.org/doi/10.1145/3007748.3018287
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