Skip to main content

Advertisement

SpringerLink
Log in

A distributed energy-efficient coverage holes detection and recovery method in wireless sensor networks using the grasshopper optimization algorithm

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

A Correction to this article was published on 18 July 2022

This article has been updated

Abstract

Maintaining coverage, power consumption, and network lifetime are the most fundamental challenges for wireless sensor networks. Since it is impossible to replace or recharge the battery of the sensor nodes, discharging the battery will end the sensor node’s life. With the death of some sensor nodes and disconnecting, the network coverage is also violated. This paper presents a method for detecting and recovering coverage holes in the wireless sensor network. In the proposed method, the network is cellulated first, and a node is selected as an agent for each cell. Then, the degree of overlap of each node’s sensing area by its neighbors is calculated to schedule sensor nodes. Based on the node overlap information, the cell agent determines cell coverage and detects holes. Finally, mobile nodes and the grasshopper optimization algorithm are used to recover the holes. The simulation results reveal that the proposed method leads to a decrease in the network’s energy consumption, an increase in network lifetime, and improved coverage in the network.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
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
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Change history

References

  • Abhilash CN , Manjula SH , Tanuja R , Venugopal KR (2021) Shortest path discovery for area coverage (spdac) using prediction-based clustering in wsn. In: Advances in artificial intelligence and data engineering, pp. 1345–1357. Springer

  • Alhaddad ZA, Manimurugan S (2021) Maximum coverage area and energy aware path planner in wsn. Materials today: proceedings

  • Balhwan S, Gupta D, Reddy SRN , et al (2019) Smart parking-a wireless sensor networks application using iot. In: Proceedings of 2nd International Conference on Communication, Computing and Networking, pp 217–230. Springer

  • Biswas S, Das R, Chatterjee P (2018) Energy-efficient connected target coverage in multi-hop wireless sensor networks. In Industry interactive innovations in science, engineering and technology, pages 411–421. Springer

  • Das S, Debbarma MK (2020) Chpt: an improved coverage-hole patching technique based on tree-center in wireless sensor networks. J Ambient Intell Hum Comput, pp 1–12

  • Dezfuli NN, Barati H (2019) Distributed energy efficient algorithm for ensuring coverage of wireless sensor networks. IET Commun 13(5):578–584

    Article  Google Scholar 

  • Fariba A, Nima JN (2017) Deployment strategies in the wireless sensor networks: systematic literature review, classification, and current trends. Wireless Pers Commun 95(2):819–846

    Article  Google Scholar 

  • Farsi M, Elhosseini MA, Badawy M, Ali Hesham A, Eldin HZ (2019) Deployment techniques in wireless sensor networks, coverage and connectivity: a survey. IEEE Access 7: 28940–28954

  • Hajjej F, Hamdi M, Ejbali R, Zaied M (2020) A distributed coverage hole recovery approach based on reinforcement learning for wireless sensor networks. Ad Hoc Netw 101:102082

    Article  Google Scholar 

  • Idrees AK, Laftah Al-Yaseen W (2021) Distributed genetic algorithm for lifetime coverage optimisation in wireless sensor networks. Int J Adv Intel Paradigm 18(1):3–24

    Google Scholar 

  • Jain JK (2020) A coherent approach for dynamic cluster-based routing and coverage hole detection and recovery in bi-layered wsn-iot. Wireless Pers Commun 114(1):519–543

    Article  Google Scholar 

  • Kandris D, Nakas C, Vomvas D, Koulouras G (2020) Applications of wireless sensor networks: an up-to-date survey. Appl Syst Innovat 3(1):14

    Article  Google Scholar 

  • Khedr AM, Osamy W, Salim A (2018) Distributed coverage hole detection and recovery scheme for heterogeneous wireless sensor networks. Comput Commun 124:61–75

  • Li K, Feng Y, Chen D, Li S (2020) A global-to-local searching-based binary particle swarm optimisation algorithm and its applications in wsn coverage optimisation. Int J Sens Netw 32(4):197–208

    Article  Google Scholar 

  • Modieginyane KM, Letswamotse BB, Malekian R, Abu-Mahfouz AM (2018) Software defined wireless sensor networks application opportunities for efficient network management: a survey. Comput Electr Eng 66: 274–287

  • Mosavifard A, Barati H (2020) An energy-aware clustering and two-level routing method in wireless sensor networks. Computing 102(7):1653–1671

    Article  MathSciNet  Google Scholar 

  • Naghibi M, Barati H (2021) Shsda: secure hybrid structure data aggregation method in wireless sensor networks. J Ambient Intell Hum Comput 12(12):10769–10788

    Article  Google Scholar 

  • Neda Nilsaz Dezfouli and Hamid Barati (2020) A distributed energy-efficient approach for hole repair in wireless sensor networks. Wireless Netw 26(3):1839–1855

    Article  Google Scholar 

  • Le Nguyen P, Nguyen K, Huy V, Ji Y (2019) Telpac: a time and energy efficient protocol for locating and patching coverage holes in wsns. J Netw Comput Appl 147:102439

    Article  Google Scholar 

  • Nie Z, Hongwei D (2021) An approximation algorithm for general energy restricted sweep coverage problem. Theor Comput Sci 864:70–79

    Article  MathSciNet  MATH  Google Scholar 

  • Osamah Ibrahim Khalaf and Bayan Mahdi Sabbar (2019) An overview on wireless sensor networks and finding optimal location of nodes. Periodic Eng Nat Sci 7(3):1096–1101

    Google Scholar 

  • Patel Nileshkumar R, Kumar Shishir (2018) Wireless sensor networks’ challenges and future prospects. In: 2018 International Conference on System Modeling & Advancement in Research Trends (SMART), pp 60–65, IEEE

  • Saremi S, Mirjalili S, Lewis A (2017) Grasshopper optimisation algorithm: theory and application. Adv Eng Softw 105:30–47

    Article  Google Scholar 

  • Sedigheh Sadat Sharifi and Hamid Barati (2021) A method for routing and data aggregating in cluster-based wireless sensor networks. Int J Commun Syst 34(7):e4754

    Google Scholar 

  • So-In C, Nguyen TG, Nguyen NG (2019) An efficient coverage hole-healing algorithm for area-coverage improvements in mobile sensor networks. Peer-to-Peer Netw Appl 12(3):541–552

  • Wang J, Ju C, Kim H-J, Sherratt RS, Lee S (2019) A mobile assisted coverage hole patching scheme based on particle swarm optimization for wsns. Cluster Comput 22(1):1787–1795

  • Yan L, He Y, Huangfu Z (2020) A fish swarm inspired holes recovery algorithm for wireless sensor networks. Int J Wireless Inf Netw 27(1):89–101

    Article  Google Scholar 

Download references

Funding

None

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran

    Ali Hallafi, Ali Barati & Hamid Barati

Authors
  1. Ali Hallafi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ali Barati
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hamid Barati
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AB and HB conceptualized the research. AH designed the experiments and collected the data and he carried out the data analysis. AB and AH validated the results. AH wrote the manuscript. AB and HB reviewed and edited the manuscript.

Corresponding author

Correspondence to Ali Barati.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

None.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hallafi, A., Barati, A. & Barati, H. A distributed energy-efficient coverage holes detection and recovery method in wireless sensor networks using the grasshopper optimization algorithm. J Ambient Intell Human Comput 14, 13697–13711 (2023). https://doi.org/10.1007/s12652-022-04024-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-022-04024-3

Keywords

Search

Navigation