research-article

Autonomous Mobile Sensor Placement in Complex Environments

Authors:

Novella Bartolini,

Tiziana Calamoneri,

Stefano Ciavarella,

Thomas La Porta,

Simone SilvestriAuthors Info & Claims

ACM Transactions on Autonomous and Adaptive Systems (TAAS), Volume 12, Issue 2

Article No.: 7, Pages 1 - 28

https://doi.org/10.1145/3050439

Published: 25 May 2017 Publication History

Abstract

In this article, we address the problem of autonomously deploying mobile sensors in an unknown complex environment. In such a scenario, mobile sensors may encounter obstacles or environmental sources of noise, so that movement and sensing capabilities can be significantly altered and become anisotropic. Any reduction of device capabilities cannot be known prior to their actual deployment, nor can it be predicted. We propose a new algorithm for autonomous sensor movements and positioning, called DOMINO (DeplOyment of MobIle Networks with Obstacles). Unlike traditional approaches, DOMINO explicitly addresses these issues by realizing a grid-based deployment throughout the Area of Interest (AoI) and subsequently refining it to cover the target area more precisely in the regions where devices experience reduced sensing. We demonstrate the capability of DOMINO to entirely cover the AoI in a finite time. We also give bounds on the number of sensors necessary to cover an AoI with asperities. Simulations show that DOMINO provides a fast deployment with precise movements and no oscillations, with moderate energy consumption. Furthermore, DOMINO provides better performance than previous solutions in all the operative settings.

References

[1]

Giuseppe Anastasi, Marco Conti, Alessio Falchi, Enrico Gregori, and Andrea Passarella. 2004. Performance measurements of mote sensor networks. In ACM Proceedings of MSWiM 2004, 174--181.

Digital Library

[2]

Amotz Bar-Noy, Theodore Brown, Matthew P. Johnson, and Ou Liu. 2009. Cheap or flexible sensor coverage. IEEE Proceedings of DCOSS, Lecture Notes in Computer Science 5516 (2009), 245--258.

Digital Library

[3]

Novella Bartolini, Giancarlo Bongiovanni, Tom La Porta, and Simone Silvestri. 2014a. On the vulnerabilities of the virtual force approach to mobile sensor deployment. IEEE Transactions on Mobile Computing (TMC) 13, 11, (2014), 2592--2605.

Digital Library

[4]

Novella Bartolini, Giancarlo Bongiovanni, Tom La Porta, Simone Silvestri, and Francesco Vincenti. 2014b. Voronoi-based deployment of mobile sensors in the face of adversaries. IEEE Proceedings of the International Conference on Communications (ICC’14).

[5]

Novella Bartolini, Tiziana Calamoneri, Annalisa Massini, and Simone Silvestri. 2011a. On adaptive density deployment to mitigate the sink-hole problem in mobile sensor networks. Springer Mobile Networks and Applications 16, 1 (2011), 134--145.

Digital Library

[6]

Novella Bartolini, Tiziana Calamoneri, Thomas F. La Porta, and Simone Silvestri. 2011b. Autonomous deployment of heterogeneous mobile sensors. IEEE Transactions on Mobile Computing (TMC) 10, 6 (2011), 753--766.

Digital Library

[7]

Tomas Beran, Richard B. Langley, Sunil B. Bisnath, and Luis Serrano. 2007. High-accuracy point positioning with low-cost GPS receivers. Navigation 54, 1 (2007), 53--63.

[8]

Nirupama Bulusu, John Heidemann, and Deborah Estrin. 2000. Gps-less low cost outdoor localization for very small devices. IEEE Personal Communications Magazine 7, 5 (October 2000), 28--34.

[9]

Jiming Chen, Shijian Li, and Youxian Sun. 2007. Novel deployment schemes for mobile sensor networks. Sensors 7 (2007), 2907--2919.

[10]

Yoann Dieudonné, Ouiddad Labbani-Igbida, and Franck Petit. 2008. Circle formation of weak mobile robots. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 3, 4, Article 16 (Dec. 2008).

Digital Library

[11]

Adriano Fagiolini, Antonio Bicchi Lisa Tani, and Gianluca Dini. 2008. Decentralized deployment of mobile sensors for optimal connected sensing coverage. In IEEE Proceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS’08). 486--491.

Digital Library

[12]

Rafael Falcon, Xu Li, and Amiya Nayak. 2011. Carrier-based focused coverage formation in wireless sensor and robot networks. IEEE Transactions on Automatic Control (TAC) 56, 10 (2011), 2406--2417.

[13]

Michele Garetto, Marco Gribaudo, Carla-Fabiana Chiasserini, and Emilio Leonardi. 2007. A distributed sensor relocation scheme for environmental control. International Conference on Mobile Ad Hoc and Sensor Systems (MASS'07).

[14]

Seth Gilbert, Nancy Lynch, Sayan Mitra, and Tina Nolte. 2009. Self-stabilizing robot formations over unreliable networks. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 4, 3, Article 17 (July 2009).

Digital Library

[15]

Hongliang Guo, Yaochu Jin, and Yan Meng. 2012. A morphogenetic framework for self-organized multirobot pattern formation and boundary coverage. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 7, 1, Article 15 (May 2012).

Digital Library

[16]

Azwirman Gusrialdi, Sandra Hirche, David Asikin, Takeshi Hatanaka, and Masayuki Fujita. 2009. Voronoi-based coverage control with anisotropic sensors and experimental case study. Intelligent Service Robotics 2 (2009), 195--204.

[17]

Nojeong Heo and Pramod K. Varshney. 2005. Energy-efficient deployment of intelligent mobile sensor networks. IEEE Transactions on Systems, Man and Cybernetics 35 (2005), 78--92.

Digital Library

[18]

Andrew Howard, Maja J. Matarić, and Gaurav S. Sukhatme. 2002. Mobile sensor network deployment using potential fields: A distributed, scalable solution to the area coverage problem. In Proceedings of the International Symposium on Distributed Autonomous Robotic Systems (DARS’02).

[19]

Khoufi Ines, Minet Pascale, Laouiti Anis, and Livolant Erwan. 2014. A simple method for the deployment of wireless sensors to ensure full coverage of an irregular area with obstacles. In Proceedings of the ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MsWIM’14). 203--210.

Digital Library

[20]

Matthew B. Johnson, Deniz Sariöz, Amotz Bar-Noy, Theodore Brown, Dinesh Verma, and Chai Wah Wu. 2009b. More is more: The benefits of denser sensor deployment. In IEEE Proceedings of the International Conference on Computer Communications (INFOCOM’09)

[21]

Wesley Kerr, Diana F. Spears, William M. Spears, and David R. Thayer. 2004. Two formal fluid models for multi-agent sweeping and obstacle avoidance. In Proceedings of the Conference on Autonomous Agents and Multiagent Systems (AAMAS’04).

[22]

Xu Li, Greg Fletcher, Amiya Nayak, and Ivan Stojmenovic. 2014. Placing sensors for area coverage in a complex environment by a team of robots. ACM Transactions on Sensor Networks (TOSN) 11, 1, Article 3 (August 2014).

Digital Library

[23]

Vladimir J. Lumelsky and Alexander A. Stepanov. 1987. Path-planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape. Algorithmica 2 (1987), 403--430.

Digital Library

[24]

Ke Ma, Yanyong Zhang, and Wade Trappe. 2008. Managing the mobility of a mobile sensor network using network dynamics. IEEE Transactions on Parallel and Distributed Systems (TPDS) 19, 1 (2008), 106--120.

Digital Library

[25]

Ming Ma and Yuanyuan Yang. 2007. Adaptive triangular deployment algorithm for unattended mobile sensor networks. IEEE Transactions on Computers (TOC) 56, 7 (2007), 946--958.

Digital Library

[26]

Sonia Martinez, Jorge Cortes, and Francesco Bullo. 2007. Motion coordination with distributed information. IEEE Control Systems Magazine (August 2007), 75--88.

[27]

Memsic MTS420/400 Datasheet. 2017. https://www.memsic.com/userfiles/files/Datasheets/WSN/mts400_420_datasheet-t.pdf, last accessed on May 2017.

[28]

Akihisa Ohya, Takayuki Ohno, and Shin’ichi Yuta. 1996. Obstacle detectability of ultrasonic ranging system and sonar map understanding. Robotics Autonomous System 18, 1 (1996), 251--257.

[29]

Celal Ozturk, Dervis Karaboga, and Beyza Gorkemli. 2011. Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm. Sensors 11 (2011), 6056--6065.

[30]

Muhammed R. Pac, Aydan M. Erkmen, and Ismet Erkmen. 2006. Scalable self-deployment of mobile sensor networks: A fluid dynamics approach. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’06).

[31]

Neal Patwari, Joshua N. Ash, Spyros Kyperountas, Alfred O. Hero, Randolph L. Moses, and Neiyer S. Correal. 2005. Locating the nodes: Cooperative localization in wireless sensor networks. IEEE Signal Processing Magazine 22, 4 (2005), 54--69.

[32]

Riverbed - OPNET Technologies. Retrieved from. http://www.riverbed.com/products/performance-management-control/.

[33]

Gabriel T. Sibley, Mohammad H. Rahimi, and Gaurav S. Sukhatme. 2002. Mobile robot platform for large-scale sensor networks. In IEEE Proceedings of the International Conference on Robotics and Automation (ICRA’02).

[34]

Guang Tan, Stephen A. Jarvis, and Anne-Marie Kermarrec. 2009a. Connectivity-guaranteed and obstacle-adaptive deployment schemes for mobile sensor networks. IEEE Transactions on Mobile Computing (TMC) 8, 6 (2009), 836--848.

Digital Library

[35]

Muhammad Tariq, Zhenyu Zhou, Yong-Jin Park, and Takuro Sato. 2010. Diffusion based self-deployment algorithm for mobile sensor networks. In IEEE Proceedings of the Vehicular Technology Conference (VTC’10).

[36]

Zhiliang Tua, Qiang Wang, Hairong Qi, and Yi Shena. 2012. Flocking based distributed self-deployment algorithms in mobile sensor networks. Journal of Parallel and Distributed Computing 72, 3 (2012), 437--449.

Digital Library

[37]

Guiling Wang, Guohong Cao, and Thomas La Porta. 2006. Movement-assisted sensor deployment. IEEE Transactions on Mobile Computing (TMC) 6 (2006), 640--652.

Digital Library

Cited By

Konovalov PMatveev AGordievich K(2025)Reactive Autonomous Ad Hoc Self-Organization of Homogeneous Teams of Unmanned Surface Vehicles for Sweep Coverage of a Passageway with an Obstacle CourseDrones10.3390/drones90301619:3(161)Online publication date: 22-Feb-2025
https://doi.org/10.3390/drones9030161
Teng R(2024)Cooperative Discovery of Failed IoT Node by Double-Zone Presentation2024 9th International Conference on Computer and Communication Systems (ICCCS)10.1109/ICCCS61882.2024.10603130(997-1001)Online publication date: 19-Apr-2024
https://doi.org/10.1109/ICCCS61882.2024.10603130
Cai XWang LHui YChen YYue WWang HZhang YCheng NLi C(2023)Coverage Optimization for Directional Sensor Networks: A Novel Sensor Redeployment SchemeIEEE Internet of Things Journal10.1109/JIOT.2022.320805610:2(1461-1475)Online publication date: 15-Jan-2023
https://doi.org/10.1109/JIOT.2022.3208056
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Index Terms

Autonomous Mobile Sensor Placement in Complex Environments
1. Networks
  1. Network architectures
  2. Network protocols

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Published In

cover image ACM Transactions on Autonomous and Adaptive Systems

ACM Transactions on Autonomous and Adaptive Systems Volume 12, Issue 2

June 2017

162 pages

ISSN:1556-4665

EISSN:1556-4703

DOI:10.1145/3099619

Editors:
Manish Parashar
Rutgers University, USA
,
Franco Zambonelli
University of Modena e Reggio Emilia, Italy

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Copyright © 2017 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 May 2017

Accepted: 01 January 2017

Revised: 01 June 2016

Received: 01 October 2015

Published in TAAS Volume 12, Issue 2

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Funding Sources

Italian Ministry of Education and University
PRIN project “AMANDA: Algorithmics for MAssive and Networked DAta.”
Hybrid Sensor Network for Emergency Critical Scenarios
NATO - North Atlantic Treaty Organization, under the SPS

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https://doi.org/10.3390/drones9030161
Teng R(2024)Cooperative Discovery of Failed IoT Node by Double-Zone Presentation2024 9th International Conference on Computer and Communication Systems (ICCCS)10.1109/ICCCS61882.2024.10603130(997-1001)Online publication date: 19-Apr-2024
https://doi.org/10.1109/ICCCS61882.2024.10603130
Cai XWang LHui YChen YYue WWang HZhang YCheng NLi C(2023)Coverage Optimization for Directional Sensor Networks: A Novel Sensor Redeployment SchemeIEEE Internet of Things Journal10.1109/JIOT.2022.320805610:2(1461-1475)Online publication date: 15-Jan-2023
https://doi.org/10.1109/JIOT.2022.3208056
Walia RSaini DShah SSrinivas MTiwari MGolla K(2023)Routing Protocols of Wireless Sensor Networks in Smart Cities2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)10.1109/ICSCDS56580.2023.10104903(1477-1482)Online publication date: 23-Mar-2023
https://doi.org/10.1109/ICSCDS56580.2023.10104903
Khalifeh ADarabkh KKhasawneh AAlqaisieh ISalameh MAlAbdala AAlrubaye SAlassaf AAl-HajAli SAl-Wardat RBartolini NBongiovannim GRajendiran K(2021)Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance EvaluationElectronics10.3390/electronics1002021810:2(218)Online publication date: 19-Jan-2021
https://doi.org/10.3390/electronics10020218
Teng R(2021)Guided Identification of Failed Nodes Based on Failure PresentationIEEE Systems Journal10.1109/JSYST.2020.297333415:1(124-133)Online publication date: Mar-2021
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Eledlebi KRuta DHildmann HSaffre FAlhammadi YIsakovic A(2020)Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment: A Voronoi-ApproachIEEE Transactions on Mobile Computing10.1109/TMC.2020.3046184(1-1)Online publication date: 2020
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Spencer SParikh AMcArthur DYoung CBlada TSlightam JBuerger S(2020)Autonomous Detection and Assessment with Moving Sensors2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS45743.2020.9340997(8231-8238)Online publication date: 24-Oct-2020
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Wang WHuang HHe FXiao FJiang XSha C(2019)An Enhanced Virtual Force Algorithm for Diverse k-Coverage Deployment of 3D Underwater Wireless Sensor NetworksSensors10.3390/s1916349619:16(3496)Online publication date: 9-Aug-2019
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Silvestri SUrgaonkar RZafer MKo B(2018)A Framework for the Inference of Sensing Measurements Based on CorrelationACM Transactions on Sensor Networks10.1145/327203515:1(1-28)Online publication date: 15-Dec-2018
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