Skip to main content

Advertisement

SpringerLink
Log in

An energy balanced and nodes aware routing protocol for energy harvesting wireless sensor networks

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

The lifetime of Wireless Sensor Networks (WSN) is a significant constraint since they are powered by non-rechargeable batteries with limited capacity. A promising solution to the energy issue is energy harvesting (EH). One of the most popular hierarchical routing protocols (RP) is the low-energy adaptive clustering hierarchy (LEACH). Most of the available RPs based on LEACH for EH-WSNs have employed the traditional cluster head (CH) selection based on taking turns, which is unsuitable. Moreover, most of them have not considered the remaining energy and harvested energy, nor investigated the weightages of these energies in selecting the CH. This work proposes the energy balanced and nodes aware (EBNA) routing protocol for EH-WSNs. It considers both the remaining energy and harvested energy along with the number of active nodes in selecting the CH which improves throughput. In addition, the weightages of the energies are investigated. EBNA is evaluated using the network simulator, GreenCastalia in OMNET. It uses the actual solar irradiance data with a resolution of 1 s. The performance is compared with energy-aware distributed clustering (EADC) and clustering routing algorithm of self-energized (CRAS) for EH-WSNs. The results show that EBNA outperforms EADC and CRAS in throughput by up to 58% and 113% and by number of CHs by up to 148% and 541%, respectively, during the high irradiance scenarios. In the low irradiance scenario, the improvement in throughput is up to 52% and 98%, and the number of CHs is up to 146% and 569%, as compared to EADC and CRAS, respectively.

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
Fig. 21

Similar content being viewed by others

References

  1. Sarkar A, Murugan TS (2019) Cluster head selection for energy efficient and delay-less routing in wireless sensor network. Wireless Netw 25(1):303–320

    Article  Google Scholar 

  2. Al-Turjman F, Altrjman C, Din S, Paul A (2019) Energy monitoring in IoT-based ad hoc networks: An overview. Comput Electr Eng 76:133–142

    Article  Google Scholar 

  3. Kompara M, Kumari S, Hölbl M (2019) Analysis and improvement of a secure key management protocol for e-health applications. Comput Electr Eng 73:97–113

    Article  Google Scholar 

  4. Msolli A, Helali A, Maaref H (2018) New security approach in real-time wireless multimedia sensor networks. Comput Electr Eng 72:910–925

    Article  Google Scholar 

  5. Jiang M, Wang H, Zhang W, Qin H, Sun X (2020) Location-based data access control scheme for Internet of Vehicles. Comput Electr Eng 86:106716

  6. Gupta BB, Quamara M (2020) An overview of Internet of Things (IoT): Architectural aspects, challenges, and protocols. Concurr Comput Pract Exp 32(21):e4946

  7. Sejdiu B, Ismaili F, Ahmedi L (2020) Integration of semantics into sensor data for the IoT: A systematic literature review. Int J Semant Web Inf Syst (IJSWIS) 16(4):1–25

    Article  Google Scholar 

  8. Zakariayi S, Babaie S (2019) DEHCIC: a distributed energy-aware hexagon based clustering algorithm to improve coverage in wireless sensor networks. Peer-to-Peer Networking and Applications 12(4):689–704

    Article  Google Scholar 

  9. Saghian M, Ravanmehr R (2019) Efficient QoS-aware middleware for resource discovery in mobile Ad Hoc networks. Adhoc Sens Wirel Netw 43

  10. Celik A, Saeed N, Shihada B, Al-Naffouri TY, Alouini MS (2019) End-to-end performance analysis of underwater optical wireless relaying and routing techniques under location uncertainty. IEEE Trans Wirel Commun

  11. Xu D, Qin Y, Zhang H, Yu L, Wang H (2019) Set-valued Kalman filtering: Event triggered communication with quantized measurements. Peer Peer Netw Appl 12(3):677–688

    Article  Google Scholar 

  12. Wu G, Chen Z, Zhang D, Liu J (2019) Resource allocation algorithm with worst case delay guarantees in energy harvesting body area networks. Peer Peer Netw Appl 12(1):74–87

    Article  Google Scholar 

  13. Deng R, Liang H, Yong J, Chai B, Yang T (2017) Distributed rate control, routing, and energy management in dynamic rechargeable sensor networks. Peer Peer Netw Appl 10(3):425–439

    Article  Google Scholar 

  14. Palani U, Alamelumangai V, Nachiappan A (2016) Hybrid routing and load balancing protocol for wireless sensor network. Wirel Netw 22(8):2659–2666

    Article  Google Scholar 

  15. Ahmed EF, Omar MA, Wan T-C, Altahir AA (2018) Work in progress: LEACH-based energy efficient routing algorithm for large-scale wireless sensor networks. J Telecommun Electron Comput Eng (JTEC) 10(1–5):83–87

    Google Scholar 

  16. Mansura A, Drieberg M, Aziz AA, Bassoo V (2019) Multi-energy threshold-based routing protocol for wireless sensor networks. In 2019 IEEE 10th Control and System Graduate Research Colloquium (ICSGRC) 71–75

  17. Brezinski K, Guevarra M, Ferens K (2020) Population based equilibrium in hybrid sa/pso for combinatorial optimization: hybrid sa/pso for combinatorial optimization. Int J Softw Sci Comput Intell (IJSSCI) 12(2):74–86

    Article  Google Scholar 

  18. Khekare G, Verma P, Dhanre U, Raut S, Sheikh S (2020) The optimal path finding algorithm based on reinforcement learning. Int J Softw Sci Comput Intell (IJSSCI) 12(4):1–18

    Article  Google Scholar 

  19. Manasrah AM, Aldomi A, Gupta BB (2019) An optimized service broker routing policy based on differential evolution algorithm in fog/cloud environment. Clust Comput 22(1):1639–1653

    Article  Google Scholar 

  20. Cao N et al (2018) Evaluation models for the nearest closer routing protocol in wireless sensor networks. IEEE Access 6:77043–77054

    Article  Google Scholar 

  21. Yang G, Jan MA, Menon VG, Shynu P, Aimal MM, Alshehri MD (2020) A centralized cluster-based hierarchical approach for green communication in a smart healthcare system. IEEE Access 8:101464–101475

    Article  Google Scholar 

  22. Ullah Z et al (2019) Energy-efficient harvested-aware clustering and cooperative routing protocol for WBAN (E-HARP). IEEE Access 7:100036–100050

    Article  Google Scholar 

  23. Rahiminasab A, Tirandazi P, Ebadi M, Ahmadian A, Salimi M (2020) An energy-aware method for selecting cluster heads in wireless sensor networks. Appl Sci 10(21):7886

    Article  Google Scholar 

  24. Haq IU et al (2020) E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks. Int J Distrib Sens Netw 16(10):1550147720968047

    Article  Google Scholar 

  25. Rani S, Balasaraswathi M, Reddy PCS, Brar GS, Sivaram M, Dhasarathan V (2020) A hybrid approach for the optimization of quality of service metrics of WSN. Wirel Netw 26(1):621–638

    Article  Google Scholar 

  26. Qureshi KN, Bashir MU, Lloret J, Leon A (2020) Optimized cluster-based dynamic energy-aware routing protocol for wireless sensor networks in agriculture precision. J Sens 2020

  27. Echoukairi H, Bourgba K, Ouzzif M (2015) A survey on flat routing protocols in wireless sensor networks. Int Symp Ubiquitous Netw Springer 311–324

    Google Scholar 

  28. Intanagonwiwat C, Govindan R, Estrin D (2000) Directed diffusion: A scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th Annual International Conference On Mobile Computing and Networking 56–67

  29. Ercan T, Asim M (2018) Energy efficient routing protocol to extend WSN lifetime. Balkan J Electr Computer Eng 6(3):178–182

    Article  Google Scholar 

  30. Al-Mousawi AJ, AL-Hassani HK (2018) A survey in wireless sensor network for explosives detection. Comput Electr Engin 72:682–701

  31. Rana KK, Tripathi S, Raw RS (2020) Link reliability-based multi-hop directional location routing in vehicular ad hoc network. Peer Peer Netw Appl 13:1656–1671

    Article  Google Scholar 

  32. Rodoplu V, Meng TH (1999) Minimum energy mobile wireless networks. IEEE J Sel Areas Commun 17(8):1333–1344

    Article  Google Scholar 

  33. Li L, Halpern JY (2001) Minimum-energy mobile wireless networks revisited. ICC 2001. IEEE Int Conf Commun 1:278–283

  34. Al-Turjman F (2019) Cognitive routing protocol for disaster-inspired internet of things. Futur Gener Comput Syst 92:1103–1115

    Article  Google Scholar 

  35. Silva A, Reza N, Oliveira A (2019) Improvement and performance evaluation of gpsr-based routing techniques for vehicular ad hoc networks. IEEE Access 7:21722–21733

    Article  Google Scholar 

  36. Silmi S, Doukha Z, Moussaoui S (2021) A self-localization range free protocol for wireless sensor networks. Peer Peer Netw Appl 1–11

  37. Elsaadany A, Khalil K (2020) Assessment of coverage quality of sensor networks for IoT applications. Peer Peer Netw Appl 13(1):320–332

    Article  Google Scholar 

  38. Mukherjee S, Amin R, Biswas G (2019) Design of routing protocol for multi-sink based wireless sensor networks. Wirel Netw 25(7):4331–4347

    Article  Google Scholar 

  39. Chan L, Chavez KG, Rudolph H, Hourani A (2020) Hierarchical routing protocols for wireless sensor network: a compressive survey. Wirel Netw 1–24

  40. Robinson YH, Julie EG, Kumar R (2019) Probability-based cluster head selection and fuzzy multipath routing for prolonging lifetime of wireless sensor networks. Peer Peer Netw Appl 12(5):1061–1075

    Article  Google Scholar 

  41. Lindsey S, Raghavendra CS (2002) PEGASIS: Power-efficient gathering in sensor information systems. Aerospc Conf Proc 3:3–3

  42. Manjeshwar A, Agrawal DP (2001) TEEN: ARouting protocol for enhanced efficiency in wireless sensor networks. In ipdps 1:189

  43. Manjeshwar A, Agrawal DP (2002) APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In ipdps Citeseer 0195b

  44. Sajwan M, Gosain D, Sharma AK (2018) Hybrid energy-efficient multi-path routing for wireless sensor networks. Comput Electr Eng 67:96–113

    Article  Google Scholar 

  45. Singh SK, Kumar P, Singh JP (2017) A survey on successors of LEACH protocol. IEEE Access 5:4298–4328

    Article  Google Scholar 

  46. Dehkordi SA, Farajzadeh K, Rezazadeh J, Farahbakhsh R, Sandrasegaran K, Dehkordi MA (2020) A survey on data aggregation techniques in IoT sensor networks. Wireless Netw 26(2):1243–1263

    Article  Google Scholar 

  47. Yukun Y, Zhilong Y, Guan W (2015) Clustering routing algorithm of self-energized wireless sensor networks based on solar energy harvesting. J China Univ Posts Telecommun 22(4):66–73

    Article  Google Scholar 

  48. Li J, Liu D (2016) An energy aware distributed clustering routing protocol for energy harvesting wireless sensor networks. In 2016 IEEE/CIC Int Conf Commun China (ICCC) 1–6

  49. Meng J, Zhang X, Dong Y, Lin X (2012) Adaptive energy-harvesting aware clustering routing protocol for wireless sensor networks. 7th Int Conf Commun Netw China 742–747

  50. Cao Y, Liu XY, Kong L, Wu MY, Khan MK (2016) EHR: Routing protocol for energy harvesting wireless sensor networks. In 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS) 56–63

  51. Bozorgi SM, Rostami AS, Hosseinabadi AAR, Balas VE (2017) A new clustering protocol for energy harvesting-wireless sensor networks. Comput Electr Eng 64:233–247

    Article  Google Scholar 

  52. Bahbahani MS, Alsusa E (2017) A cooperative clustering protocol with duty cycling for energy harvesting enabled wireless sensor networks. IEEE Trans Wirel Commun 17(1):101–111

    Article  Google Scholar 

  53. Muhammad UB, Ezugwu AE, Ofem PO, Rajamäki J, Aderemi AO (2017) Energy neutral protocol based on hierarchical routing techniques for energy harvesting wireless sensor network. AIP Conf Proc 1836(1):020025

  54. Xiao M, Zhang X, Dong Y (2013) An effective routing protocol for energy harvesting wireless sensor networks. IEEE Wirel Commun Netw Conf (WCNC) 2080–2084

  55. Instruments T (2006) CC2420: 2.4 GHz IEEE 802.15. 4/ZigBee-ready RF Transceiver

  56. Yang D (2018) SolarData: An R package for easy access of publicly available solar datasets. Sol Energy 171:A3–A12

    Article  Google Scholar 

  57. Sengupta M, Andreas A (2010) Oahu Solar Measurement Grid (1-Year Archive): 1-Second Solar Irradiance; Oahu, Hawaii (Data); NREL Report No. DA-5500-56506. https://doi.org/10.5439/1052451

  58. Futurlec (2021) https://www.futurlec.com/solar/szgd6030.shtml. Accessed 23 Nov 2021

  59. Texas Instruments (2021) http://www.ti.com/product/ CC2420. Accessed 23 Nov 2021

Download references

Funding

The work was supported by the Universiti Teknologi PETRONAS undergraduate assistantship (GA) scheme.

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Universiti Teknologi Petronas, 32610, Bandar Seri Iskandar, Malaysia

    Anika Mansura, Micheal Drieberg & Azrina Abd Aziz

  2. Department of Electrical and Electronic Engineering, University of Mauritius, Reduit, 80837, Mauritius

    Vandana Bassoo

  3. Faculty of Technical Sciences, University of Novi Sad, 21000, Novi Sad, Serbia

    Sohail Sarang

Authors
  1. Anika Mansura
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Micheal Drieberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Azrina Abd Aziz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vandana Bassoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sohail Sarang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Anika Mansura: Writing the original draft, Conceptualization, Programming, Investigation, Technical Analysis. Micheal Drieberg: Supervision, Conceptualization, Methodology, Investigation, Technical Analysis, Review. Azrina Abd Aziz: Supervision, Validation, Review. Vandana Bassoo: Supervision, Review. Sohail Sarang: Technical Analysis, Review.

Corresponding author

Correspondence to Anika Mansura.

Ethics declarations

Conflicts of interest

The authors have declared that there are no conflicts of interest regarding the publication of the paper.

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

Mansura, A., Drieberg, M., Aziz, A.A. et al. An energy balanced and nodes aware routing protocol for energy harvesting wireless sensor networks. Peer-to-Peer Netw. Appl. 15, 1255–1280 (2022). https://doi.org/10.1007/s12083-022-01292-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-022-01292-w

Keywords

Search

Navigation