research-article

Optimizing sensor movement planning for energy efficiency

Authors:

Mary Jane Irwin,

Wensheng Zhang,

Tom La PortaAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 7, Issue 4

Article No.: 33, Pages 1 - 17

https://doi.org/10.1145/1921621.1921627

Published: 04 February 2011 Publication History

Abstract

Conserving the energy for motion is an important yet not-well-addressed problem in mobile sensor networks. In this article, 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 trapezoidal velocity schedule for minimizing energy consumption when the road condition is uniform; and a corresponding 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

Santoshi G(2023)Mobile Sensor Nodes Traversal Schemes to Attend Events at Random Locations With Minimal Energy DepletionIEEE Access10.1109/ACCESS.2023.323857611(9221-9231)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3238576
Regis Anne W. (2019)Energy-Efficient Mobility Heuristics for Maximizing Network Lifetime in Robotic Wireless Sensor NetworksHandbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization10.4018/978-1-5225-7335-7.ch019(426-452)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-7335-7.ch019
Bampas ECzyzowicz JIlcinkas DKlasing R(2019)Beachcombing on strips and islandsTheoretical Computer Science10.1016/j.tcs.2019.04.001Online publication date: Apr-2019
https://doi.org/10.1016/j.tcs.2019.04.001
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 Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 7, Issue 4

February 2011

252 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1921621

Issue’s Table of Contents

Copyright © 2011 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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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 04 February 2011

Accepted: 01 July 2010

Revised: 01 July 2010

Received: 01 February 2009

Published in TOSN Volume 7, Issue 4

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Cited By

Santoshi G(2023)Mobile Sensor Nodes Traversal Schemes to Attend Events at Random Locations With Minimal Energy DepletionIEEE Access10.1109/ACCESS.2023.323857611(9221-9231)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3238576
Regis Anne W. (2019)Energy-Efficient Mobility Heuristics for Maximizing Network Lifetime in Robotic Wireless Sensor NetworksHandbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization10.4018/978-1-5225-7335-7.ch019(426-452)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-7335-7.ch019
Bampas ECzyzowicz JIlcinkas DKlasing R(2019)Beachcombing on strips and islandsTheoretical Computer Science10.1016/j.tcs.2019.04.001Online publication date: Apr-2019
https://doi.org/10.1016/j.tcs.2019.04.001
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
Czyzowicz JGodon MKranakis ELabourel A(2018)Group search of the plane with faulty robotsTheoretical Computer Science10.1016/j.tcs.2018.09.029Online publication date: Oct-2018
https://doi.org/10.1016/j.tcs.2018.09.029
Suh JGong JOh S(2017)Fast Sampling-Based Cost-Aware Path Planning With Nonmyopic Extensions Using Cross EntropyIEEE Transactions on Robotics10.1109/TRO.2017.273866433:6(1313-1326)Online publication date: Dec-2017
https://doi.org/10.1109/TRO.2017.2738664
Senturk IAkkaya KJanansefat S(2016)Towards realistic connectivity restoration in partitioned mobile sensor networksInternational Journal of Communication Systems10.1002/dac.281929:2(230-250)Online publication date: 25-Jan-2016
https://dl.acm.org/doi/10.1002/dac.2819
Sun CTang QLi X(2015)Energy-efficient link selection scheme in a two-hop relay scenario with considering a mobile relayIET Communications10.1049/iet-com.2015.00969:18(2287-2292)Online publication date: 17-Dec-2015
https://doi.org/10.1049/iet-com.2015.0096
Czyzowicz JGąsieniec LGeorgiou KKranakis EMacQuarrie F(2015)The Beachcombers' ProblemTheoretical Computer Science10.1016/j.tcs.2015.09.011608:P3(201-218)Online publication date: 10-Dec-2015
https://dl.acm.org/doi/10.1016/j.tcs.2015.09.011
Bampas ECzyzowicz JIlcinkas DKlasing R(2015)Beachcombing on Strips and IslandsRevised Selected Papers of the 11th International Symposium on Algorithms for Sensor Systems - Volume 953610.1007/978-3-319-28472-9_12(155-168)Online publication date: 17-Sep-2015
https://dl.acm.org/doi/10.1007/978-3-319-28472-9_12
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