research-article

Joint Coverage, Connectivity, and Charging Strategies for Distributed UAV Networks

Authors:

Marco Di Felice,

Federico Montori,

Kaushik R. Chowdhury,

Luciano BononiAuthors Info & Claims

IEEE Transactions on Robotics, Volume 34, Issue 4

Pages 883 - 900

https://doi.org/10.1109/TRO.2018.2839087

Published: 01 August 2018 Publication History

Abstract

This paper proposes deployment strategies for consumer unmanned aerial vehicles (UAVs) to maximize the stationary coverage of a target area and to guarantee the continuity of the service through energy replenishment operations at ground charging stations. The three main contributions of our work are as follows. 1) A centralized optimal solution is proposed for the joint problem of UAV positioning for a target coverage ratio and scheduling the charging operations of the UAVs that involves travel to the ground station. 2) A distributed game-theory-based scheduling strategy is proposed using normal-form games with rigorous analysis on performance bounds. Furthermore, a bio-inspired scheme using attractive/repulsive spring actions are used for distributed positioning of the UAVs. 3) The cost-benefit tradeoffs of different levels of cooperation among the UAVs for the distributed charging operations is analyzed. This paper demonstrates that the distributed deployment using only 1-hop messaging achieves approximation of the centrally computed optimum, in terms of coverage and lifetime.

References

[1]

<institution content-type=institution>Valour consultancy</institution>, The future of commercial and industrial UAVs. Brochure, 2016. {Online}. Available: http://www.valourconsultancy.com/wp-content/uploads/2015/12/The-Future-of-UAVs-Drones-Report-Brochure.pdf

[2]

B. D. Song, J. Kim, J. Kim, H. Park, J. R. Morrison, and D. H. Shim, “ Persistent UAV service: An improved scheduling formulation and prototypes of system components,” J. Intell. Robot. Syst., vol. Volume 74, no. Issue 1, pp. 221–232, 2014.

Digital Library

[3]

H. Shakhatreh, A. Khreishah, J. Chakareski, H. B. Salameh, and I. Khalil, “ On the continuous coverage problem for a swarm of UAVs,” in Proc. 37th IEEE Sarnoff Symp., Princeton, NJ, USA, 2016, pp. 130–135.

[4]

A. Trotta, M. Di Felice, K. Chowdhury, and L. Bononi, “ Fly and recharge: Achieving persistent coverage using small unmanned aerial vehicles (SUAVs),” in Proc. IEEE Int. Conf. Commun., Paris, France, 2017, pp. 1–7.

[5]

M. Erdelj, E. Natalizio, K. R. Chowdhury, and I. F. Akyildiz, “ Help from the Sky: Leveraging UAVs for disaster management,” IEEE Pervasive Comput., vol. Volume 16, no. Issue 1, pp. 24–32, 2017.

Digital Library

[6]

A. Osseiran et al., “ Scenarios for 5G mobile and wireless communications; the vision of the METIS project,” IEEE Commun. Mag., vol. Volume 52, no. Issue 5, pp. 26–35, 2014.

[7]

Y. Zeng, R. Zhang, and T. J. Lim, “ Wireless communications with unmanned aerial vehicles: Opportunities and challenges,” IEEE Commun. Mag., vol. Volume 54, no. Issue 5, pp. 36–42, 2016.

Digital Library

[8]

M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “ Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage,” IEEE Commun. Lett., vol. Volume 20, no. Issue 8, pp. 1647–1650, 2016.

[9]

M. Di Felice, A. Trotta, L. Bedogni, K. R. Chowdhury, and L. Bononi, “ Self-organizing aerial mesh networks for emergency communication,” in Proc. IEEE 25th Annu. Int. Symp. Pers., Indoor, Mobile Radio Commun., Washington, DC, USA, 2014, pp. 1631–1636.

[10]

J. Yu, S. J. Chung, and P. G. Voulgaris, “ Target assignment in robotic networks: Distance optimality guarantees and hierarchical strategies,” IEEE Trans. Autom. Control, vol. Volume 60, no. Issue 2, pp. 327–341, 2015.

[11]

K. Derr and M. Manic, “ Extended virtual spring mesh (EVSM): The distributed self-organizing mobile ad hoc network for area exploration,” IEEE Trans. Ind. Electron., vol. Volume 58, no. Issue 12, pp. 5424–5437, 2011.

[12]

M. Asadpour, B. Van den Bergh, D. Giustiniano, K. A. Hummel, S. Pollin, and B. Plattner, “ Micro aerial vehicle networks: An experimental analysis of challenges and opportunities,” IEEE Commun. Mag., vol. Volume 52, no. Issue 7, pp. 141–149, 2014.

[13]

R. Shinkuma and Y. Goto, “ Wireless multihop networks formed by unmanned aerial vehicles with separable access points and replaceable batteries,” in Proc. IEEE 7th Annu. Ubiquitous Comput. Mobile Commun. Conf., New York, NY, USA, 2016, pp. 1–6.

[14]

J. Leonard, A. Savvaris, and A. Tsourdos, “ Energy management in swarm of unmanned aerial vehicles,” in Proc. Int. Conf. Unmanned Aircraft Syst., 2013, pp. 124–133.

[15]

L. Gupta, R. Jain, and G. Vaszkun, “ Survey of important issues in UAV communication networks,” IEEE Commun. Surveys Tut., vol. Volume 18, no. Issue 2, pp. 1123–1152, Secondquarter 2016.

Digital Library

[16]

D. Halperin, B. Greenstein, A. Sheth, and D. Wetherall, “ Demystifying 802.11n power consumption,” in Proc. IEEE HotPower, Vancouver, BC, Canada, 2010, pp. 1–5.

Digital Library

[17]

J. Kim, B. D. Song, and J. R. Morrison, “ On the scheduling of systems of UAVs and fuel service stations for long-term mission fulfillment,” J. Intell. Robot Syst., vol. Volume 70, no. Issue 1, pp. 347–359, 2013.

Digital Library

[18]

J. Scherer and B. Rinner, “ Persistent multiUAV surveillance with energy and communication constraints,” in Proc. IEEE Int. Conf. Autom. Sci. Eng., Fort Worth, TX, USA, 2016, pp. 1225–1230.

[19]

“ The Role of Deployable Aerial Communications Architecture in Emergency Communications and Recommended Next Steps,” White Paper, Federal Communications Commission (FCC), Washington, DC, USA, 2011.

[20]

S. Morgenthaler, T. Braun, Z. Zhao, T. Staub, and M. Anwander, “ UAVNet: A mobile wireless mesh network using unmanned aerial vehicles,” in Proc. IEEE Globecom Workshops, Anaheim, CA, USA, 2012, pp. 1603–1608.

[21]

M. Alzenad, A. El-Key, F. Lagum, and H. Yanikomeroglu, “ 3-D placement of an unmanned aerial vehicle base station (UAV-BS) for energy-efficient maximal coverage,” IEEE Commun. Lett., vol. Volume 6, no. Issue 4, pp. 434–437, 2017.

[22]

E. Yanmaz, “ Connectivity versus area coverage in unmanned aerial vehicle networks,” in Proc. IEEE Int. Conf. Commun., Ottawa, ON, Canada, 2012, pp. 719–723.

[23]

C. Di Franco and G. Buttazzo, “ Energy-aware coverage path planning of UAVs,” in Proc. IEEE Int. Conf. Auton. Robot Syst. Competitions, Vila Real, Portugal, 2015, pp. 111–117.

Digital Library

[24]

K. Daniel, S. Rohde, N. Goddemeier, and C. Wietfield, “ Cognitive agent mobility for aerial sensor networks,” IEEE Sensors J., vol. Volume 11, no. Issue 11, pp. 2671–2682, 2013.

[25]

N. Nigam, S. Bicniawski, I. Kroo, and J. Vian, “ Control of multiple UAVs for persistent surveillance: Algorithm and flight test results,” IEEE Trans. Control Syst. Technol., vol. Volume 20, no. Issue 5, pp. 1236–1251, 2012.

[26]

C.-I. Vasile and C. Belta, “ An automata-theoretic approach to the vehicle routing problem,” in Proc. Robot. Sci. Syst., 2014, pp. 1–9.

[27]

K. A. Swieringa et al., “ Autonomous battery swapping systems for small-scale helicopters,” in Proc. IEEE Int. Conf. Robot. Autom., Anchorage, AK, USA, 2010, pp. 3335–3340.

[28]

K. Yu, A. K. Budhiraja, and P. Tokekar, “ Algorithms for routing of unmanned aerial vehicles with mobile recharging stations and for package delivery,” Computing Research Repository (CoRR), arXiv:1704.00079v3, 2017.

[29]

N. Mathew, S. L. Smith, and S. L. Waslander, “ Multirobot rendezvous planning for recharging in persistent tasks,” IEEE Trans. Robot., vol. Volume 31, no. Issue 1, pp. 128–142, 2015.

Digital Library

[30]

N. K. Ure, G. Chowdhary, T. Toksoz, J. P. How, M. A. Vavrina, and J. Vian, “ An automated battery management system to enable persistent missions with multiple aerial vehicles,” IEEE/ASME Trans. Mechatronics, vol. Volume 20, no. Issue 1, pp. 275–286, 2015.

[31]

K. Dorling, J. Heinrichs, G. G. Messier, and S. Magierowski, “ Vehicle routing problems for drone delivery,” IEEE Trans. Syst., Man, Cybern., Syst., vol. Volume 47, no. Issue 1, pp. 70–85, 2017.

[32]

H. Zhang, Z. Zhang, and H. Dai, “ Gossip-based information spreading in mobile networks,” IEEE Trans. Wireless Commun., vol. Volume 12, no. Issue 11, pp. 5918–5928, 2013.

[33]

S. Vasudevan, J. Kurose, and D. Towsley, “ Design and analysis of a leader election algorithm for mobile ad hoc networks,” in Proc. 12th IEEE Int. Conf. Netw. Protocols, 2004, pp. 350–360.

Digital Library

[34]

B. Wang, H. B. Lim, and D. Ma, “ A survey of movement strategies for improving network coverage in wireless sensor networks,” Comput. Commun., vol. Volume 32, no. Issue 1, pp. 1427–1436, 2009.

Digital Library

[35]

M. J. Osborne, An Introduction to Game Theory, vol. Volume 3, no. Issue 3. New York, NY, USA: Oxford Univ. Press, 2004.

[36]

{Online}. Available: http://omnetpp.org. {Accessed on: 2018}.

Cited By

Yang XWang CLiang JZhao JYue KLi W(2024)Research on path planning in UAV-assisted emergency communicationEURASIP Journal on Wireless Communications and Networking10.1186/s13638-024-02413-02024:1Online publication date: 7-Nov-2024
https://dl.acm.org/doi/10.1186/s13638-024-02413-0
Betalo MLeng SAbishu HSeid AFakirah MErbad AGuizani M(2024)Multi-Agent DRL-Based Energy Harvesting for Freshness of Data in UAV-Assisted Wireless Sensor NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2024.345421721:6(6527-6541)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TNSM.2024.3454217
Jin XLuo ZShi JWang L(2024)Two-layer intelligent deployment of capsule airports and unmanned aerial vehicles for providing emergency communication servicesExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121795238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121795
Show More Cited By

Recommendations

Integrated Connectivity and Coverage Techniques for Wireless Sensor Networks
MobiWac '16: Proceedings of the 14th ACM International Symposium on Mobility Management and Wireless Access

A wireless sensor network (WSN) consists of a group of energy-constrained sensor nodes with the ability of both sensing and communication, which can be deployed in a field of interesting (FoI) for detecting or monitoring some special events and then ...
A Novel UAV Charging Scheme for Minimizing Coverage Breach in Rechargeable Sensor Networks
Green, Pervasive, and Cloud Computing
Abstract
In wireless rechargeable sensor networks, one of the most important issues is how and when to recharge the sensor nodes. Existing studies show that not all of the sensors can be properly recharged in time due to the limitation of solar or wind-...
Distributed coverage and connectivity in three dimensional wireless sensor networks
IWCMC '10: Proceedings of the 6th International Wireless Communications and Mobile Computing Conference

This paper investigates coverage and connectivity issues for Wireless Sensor Networks (WSNs) under three dimensional deployment scenarios. WSNs are deployed over a region to sense the events of interest in a geographical area and transmit collected data ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Transactions on Robotics

IEEE Transactions on Robotics Volume 34, Issue 4

August 2018

306 pages

ISSN:1552-3098

Issue’s Table of Contents

Copyright © 2018.

Publisher

IEEE Press

Publication History

Published: 01 August 2018

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

37
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Yang XWang CLiang JZhao JYue KLi W(2024)Research on path planning in UAV-assisted emergency communicationEURASIP Journal on Wireless Communications and Networking10.1186/s13638-024-02413-02024:1Online publication date: 7-Nov-2024
https://dl.acm.org/doi/10.1186/s13638-024-02413-0
Betalo MLeng SAbishu HSeid AFakirah MErbad AGuizani M(2024)Multi-Agent DRL-Based Energy Harvesting for Freshness of Data in UAV-Assisted Wireless Sensor NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2024.345421721:6(6527-6541)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TNSM.2024.3454217
Jin XLuo ZShi JWang L(2024)Two-layer intelligent deployment of capsule airports and unmanned aerial vehicles for providing emergency communication servicesExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121795238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121795
Zhang TWang YSun MChen Z(2024)Air combat maneuver decision based on deep reinforcement learning with auxiliary rewardNeural Computing and Applications10.1007/s00521-024-09720-z36:21(13341-13356)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00521-024-09720-z
Zhou LLeng SWang QLiu Q(2023)Integrated Sensing and Communication in UAV Swarms for Cooperative Multiple Targets TrackingIEEE Transactions on Mobile Computing10.1109/TMC.2022.319349922:11(6526-6542)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1109/TMC.2022.3193499
Wang THuang PDong GZhao Y(2023)A Diffusion-Based Reactive Approach to Road Network Cooperative Persistent SurveillanceIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.332900125:5(4265-4277)Online publication date: 21-Nov-2023
https://dl.acm.org/doi/10.1109/TITS.2023.3329001
Alam MMoh S(2023)Q-learning-based routing inspired by adaptive flocking control for collaborative unmanned aerial vehicle swarmsVehicular Communications10.1016/j.vehcom.2023.10057240:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.vehcom.2023.100572
Ojha TRaptis TPassarella AConti M(2023)Wireless power transfer with unmanned aerial vehiclesPervasive and Mobile Computing10.1016/j.pmcj.2023.10182093:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.pmcj.2023.101820
Sun ZWang NLin HZhou X(2023)Persistent coverage of UAVs based on deep reinforcement learning with wonderful life utilityNeurocomputing10.1016/j.neucom.2022.11.091521:C(137-145)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1016/j.neucom.2022.11.091
Liu LYang J(2023)Dynamic operations and maintenance of an unmanned aerial vehicle swarm for continuous emergency communicationComputers and Industrial Engineering10.1016/j.cie.2023.109564184:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.cie.2023.109564
Show More Cited By

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents