research-article

A distributed adaptive sampling soluting using autonomous underwater vehicles

Authors:

Dario PompiliAuthors Info & Claims

WUWNet '12: Proceedings of the 7th International Conference on Underwater Networks & Systems

Article No.: 29, Pages 1 - 8

https://doi.org/10.1145/2398936.2398974

Published: 05 November 2012 Publication History

Abstract

To achieve efficient and cost-effective sensing coverage of the vast under-sampled 3D aquatic volume, intelligent adaptive sampling strategies involving a team of Autonomous Underwater Vehicles (AUVs) endowed with underwater wireless communication capabilities become essential. Given a 3D field of interest to sample, the AUVs should coordinate to take measurements using minimal resources (time or energy) in order to reconstruct the field at an onshore station with admissible error. A novel distributed adaptive sampling solution that can minimize the sampling cost (in terms of time or energy expenditure) is proposed along with underwater acoustic communication protocols that facilitate the coordination of the vehicles. The proposed solution operates in two distinct phases in which it employs random compressive sensing (Phase I) and adaptive sampling (Phase II). Phase I captures the spatial distribution of the field of interest while Phase II tracks the temporal variation of the same. A distributed framework for multi-vehicle adaptive sampling that facilitates the movement of data between AUVs and enables compute intensive adaptive sampling algorithms is proposed. Simulation results on real data traces show that the proposed adaptive sampling solution significantly outperforms existing solutions in terms of reconstruction accuracy and energy expenditure.

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Cited By

S ADhongdi S(2022)Multiple AUVs for Ocean Phenomena Monitoring: A Review2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)10.1109/CCNC49033.2022.9700726(1-7)Online publication date: 8-Jan-2022
https://dl.acm.org/doi/10.1109/CCNC49033.2022.9700726
Sun JLiu SZhang FSong AYu JZhang A(2021)A Kriged Compressive Sensing Approach to Reconstruct Acoustic Fields From Measurements Collected by Underwater VehiclesIEEE Journal of Oceanic Engineering10.1109/JOE.2020.297427046:1(294-306)Online publication date: Jan-2021
https://doi.org/10.1109/JOE.2020.2974270
Rahmati MNadeem MSadhu VPompili D(2019)UW-MARLProceedings of the 14th International Conference on Underwater Networks & Systems10.1145/3366486.3366533(1-5)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3366486.3366533
Show More Cited By

Index Terms

A distributed adaptive sampling soluting using autonomous underwater vehicles
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Networks

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Published In

cover image ACM Conferences

WUWNet '12: Proceedings of the 7th International Conference on Underwater Networks & Systems

November 2012

243 pages

ISBN:9781450317733

DOI:10.1145/2398936

General Chairs:
Mario Gerla
University of California, Los Angeles
,
T. C. Yang
National Sun Yet-Sen University, Taiwan
,
Program Chairs:
Tommaso Melodia
State University of New York at Buffalo
,
Liuqing Yang
Colorado State University

Copyright © 2012 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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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Published: 05 November 2012

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Office of Cyberinfrastructure

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WUWNET '12

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SIGMOBILE

WUWNET '12: Conference on Under Water Networks

November 5 - 6, 2012

California, Los Angeles

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Overall Acceptance Rate 84 of 180 submissions, 47%

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Cited By

S ADhongdi S(2022)Multiple AUVs for Ocean Phenomena Monitoring: A Review2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)10.1109/CCNC49033.2022.9700726(1-7)Online publication date: 8-Jan-2022
https://dl.acm.org/doi/10.1109/CCNC49033.2022.9700726
Sun JLiu SZhang FSong AYu JZhang A(2021)A Kriged Compressive Sensing Approach to Reconstruct Acoustic Fields From Measurements Collected by Underwater VehiclesIEEE Journal of Oceanic Engineering10.1109/JOE.2020.297427046:1(294-306)Online publication date: Jan-2021
https://doi.org/10.1109/JOE.2020.2974270
Rahmati MNadeem MSadhu VPompili D(2019)UW-MARLProceedings of the 14th International Conference on Underwater Networks & Systems10.1145/3366486.3366533(1-5)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3366486.3366533
Pandey PPompili D(2013)Distributed Computing Framework for Underwater Acoustic Sensor NetworksProceedings of the 2013 IEEE International Conference on Distributed Computing in Sensor Systems10.1109/DCOSS.2013.76(318-320)Online publication date: 20-May-2013
https://dl.acm.org/doi/10.1109/DCOSS.2013.76

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