[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Log in

A heuristic node placement strategy for extending network lifetime and ensuring target coverage in mobile wireless sensor networks

  • Research Paper
  • Published:
Evolutionary Intelligence Aims and scope Submit manuscript

Abstract

Prolonging network lifetime has long been one of the most critical challenges in designing wireless sensor networks in general and mobile wireless sensor networks in particular. Regarding network lifetime, one of the factors affecting it the most is energy efficiency. In a mobile wireless sensor network, compared to stationary ones, energy management has an even greater impact on the network lifetime since the movement of the sensors drains an enormous amount of energy. Moreover, in target-based wireless sensor networks, it is mandatory to ensure target coverage along with lifetime optimization. In this paper, we investigate a mobile sensor network model where stationary targets must be continuously monitored by mobile sensors. In order to maximize network lifetime and guarantee the coverage of all targets in the monitoring region, we take sensor nodes’ movement into account. We propose the Lifetime Effective Movement Algorithm, a novel heuristic approach consisting of determining the optimal regions for sensor deployment and scheduling sensor nodes’ movement, to address this issue. Experimental results demonstrate that our proposed algorithm outperforms two existing approaches in terms of network lifetime with an improvement varying from 125% to 269%. Moreover, the proposed method produces an approximation ratio in the range of 82.14-\(-\)88.41% compared to the exact solution.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Algorithm 1
Algorithm 2
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data Availability

The authors declare that the data supporting the findings of this study are available at https://github.com/nguyenphuctan-dev/mwsn-lifetime-experiment-data.

References

  1. Jagtap AM, Gomathi N (2017) Minimizing sensor movement in target coverage problem: A hybrid approach using Voronoi partition and swarm intelligence. Bullet Polish Acad Sci Tech Sci 65(2):263–272

    Google Scholar 

  2. Wang Q, Liu W, Wang T, Zhao M, Li X, Xie M, Ma M, Zhang G, Liu A (2019) Reducing delay and maximizing lifetime for wireless sensor networks with dynamic traffic patterns. IEEE Access 7:70212–70236

    Article  Google Scholar 

  3. El Alami H, Najid A (2019) Ech: An enhanced clustering hierarchy approach to maximize lifetime of wireless sensor networks. IEEE Access 7:107142–107153

    Article  Google Scholar 

  4. Ahmed MM, Houssein EH, Hassanien AE, Taha A, Hassanien E (2019) Maximizing lifetime of large-scale wireless sensor networks using multi-objective whale optimization algorithm. Telecommun Syst 72(2):243–259

    Article  Google Scholar 

  5. Zhong J, Huang Z, Feng L, Du W, Li Y (2020) A hyper-heuristic framework for lifetime maximization in wireless sensor networks with a mobile sink. IEEE/CAA J Automatica Sinica 7(1):223–236

    Article  Google Scholar 

  6. Chen Z-G, Lin Y, Gong Y-J, Zhan Z-H, Zhang J (2021) Maximizing lifetime of range-adjustable wireless sensor networks: A neighborhood-based estimation of distribution algorithm. IEEE Trans Cybern 51(11):5433–5444

    Article  Google Scholar 

  7. Luo C, Hong Y, Li D, Wang Y, Chen W, Hu Q (2020) Maximizing network lifetime using coverage sets scheduling in wireless sensor networks. Ad Hoc Netw 98:102037

    Article  Google Scholar 

  8. Guimaraes DA et al (2016) Increasing the lifetime of mobile WSNs via dynamic optimization of sensor node communication activity. Sensors 16(9):1536

    Article  Google Scholar 

  9. Gao X, Chen Z, Wu F, Chen G (2017) Energy efficient algorithms for \(k\) -sink minimum movement target coverage problem in mobile sensor network. IEEE/ACM Trans Netw 25(6):3616–3627

    Article  Google Scholar 

  10. Zhang X, Lu X, Zhang X (2020) Mobile wireless sensor network lifetime maximization by using evolutionary computing methods. Ad Hoc Netw 101:102094

    Article  Google Scholar 

  11. Hanh NT, Binh HTT, Van Son N, Lan PN (2019) Minimal node placement for ensuring target coverage with network connectivity and fault tolerance constraints in wireless sensor networks. In: 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 2923–2930

  12. Hanh NT, Le Nguyen P, Tuyen PT, Binh HTT, Kurniawan E, Ji Y (2018) Node placement for target coverage and network connectivity in wsns with multiple sinks. In: 2018 15th IEEE annual consumer communications & networking conference (CCNC), pp. 1–6

  13. Nguyen PL, Hanh NT, Khuong NT, Binh HTT, Ji Y (2019) Node placement for connected target coverage in wireless sensor networks with dynamic sinks. Pervasive Mob Comput 59:101070

    Article  Google Scholar 

  14. Liu H, Chu X, Leung Y-W, Du R (2013) Minimum-cost sensor placement for required lifetime in wireless sensor-target surveillance networks. IEEE Trans Parallel Distrib Syst 24(9):1783–1796

    Article  Google Scholar 

  15. Saadi N, Bounceur A, Euler R, Lounis M, Bezoui M, Kerkar M, Pottier B (2020) Maximum lifetime target coverage in wireless sensor networks. Wireless Pers Commun 111(3):1525–1543

    Article  Google Scholar 

  16. Balaji S, Anitha M, Rekha D, Arivudainambi D (2020) Energy efficient target coverage for a wireless sensor network. Measurement 165:108167

    Article  Google Scholar 

  17. Asadollahi H, Zandi S, Asharioun H (2022) Maximizing network lifetime in many-to-one wireless sensor networks (wsns). Wireless Pers Commun 123(4):2971–2983

    Article  Google Scholar 

  18. Dattatraya KN, Rao KR (2022) Hybrid based cluster head selection for maximizing network lifetime and energy efficiency in WSN. J King Saud University-Comput Inform Sci 34(3):716–726

    Google Scholar 

  19. Akram J et al (2022) Using adaptive sensors for optimised target coverage in wireless sensor networks. Sensors 22(3):1083

    Article  Google Scholar 

  20. Na Mottaki, Motameni H, Mohamadi H (2023) An effective hybrid genetic algorithm and tabu search for maximizing network lifetime using coverage sets scheduling in wireless sensor networks. J Supercomput 79(3):3277–3297

    Article  Google Scholar 

  21. Liao Z, Wang J, Zhang S, Cao J, Min G (2015) Minimizing movement for target coverage and network connectivity in mobile sensor networks. IEEE Trans Parallel Distrib Syst 26(7):1971–1983

    Article  Google Scholar 

  22. Gil J-M, Han Y-H (2011) A target coverage scheduling scheme based on genetic algorithms in directional sensor networks. Sensors 11(2):1888–1906

    Article  Google Scholar 

  23. Mikitiuk A, Trojanowski K (2020) Maximization of the sensor network lifetime by activity schedule heuristic optimization. Ad Hoc Netw 96:101994

    Article  Google Scholar 

  24. Tretyakova A, Seredynski F (2013) Application of evolutionary algorithms to maximum lifetime coverage problem in wireless sensor networks. In: 2013 IEEE international symposium on parallel & distributed processing, workshops and Phd forum, pp. 445–453

  25. Tabibi S, Ghaffari A (2019) Energy-efficient routing mechanism for mobile sink in wireless sensor networks using particle swarm optimization algorithm. Wireless Pers Commun 104(1):199–216

    Article  Google Scholar 

  26. Wang J et al (2019) Energy efficient routing algorithm with mobile sink support for wireless sensor networks. Sensors 19(7):1494

    Article  Google Scholar 

  27. Hanh NT, Binh HTT, Hoai NX, Palaniswami MS (2019) An efficient genetic algorithm for maximizing area coverage in wireless sensor networks. Inf Sci 488:58–75

    Article  MathSciNet  Google Scholar 

  28. Guo J, Jafarkhani H (2019) Movement-efficient sensor deployment in wireless sensor networks with limited communication range. IEEE Trans Wireless Commun 18(7):3469–3484

    Article  Google Scholar 

  29. El-Moukaddem F, Torng E, Xing G (2013) Mobile relay configuration in data-intensive wireless sensor networks. IEEE Trans Mob Comput 12(2):261–273

    Article  Google Scholar 

  30. Mikhaylov K, Tervonen J (2013) Energy consumption of the mobile wireless sensor network’s node with controlled mobility. In: 2013 27th international conference on advanced information networking and applications workshops, pp. 1582–1587

  31. IEEE Draft Standard for Information Technology – Telecommunications and Information Exchange Between Systems Local and Metropolitan Area Networks – Specific Requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. IEEE P802.11-REVmd/D3.0, October 2019, 1–4647 (2019). https://ieeexplore.ieee.org/servlet/opac?punumber=8906265, [Online; accessed 01-June-2023]

  32. Del-Valle-Soto C et al (2020) Wireless sensor network energy model and its use in the optimization of routing protocols. Energies 13(3):728

    Article  Google Scholar 

Download references

Acknowledgements

This research is funded by Ministry of Education and Training under project number B2023.DNA.13.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nguyen Thi Hanh.

Ethics declarations

Conflict of interest

The authors have no Conflict of interest to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Binh, H.T.T., Hanh, N.T., Tan, N.P. et al. A heuristic node placement strategy for extending network lifetime and ensuring target coverage in mobile wireless sensor networks. Evol. Intel. 17, 3151–3168 (2024). https://doi.org/10.1007/s12065-024-00916-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12065-024-00916-9

Keywords

Navigation