Skip to main content

Advertisement

SpringerLink
Log in

Multi-QoS constraint multipath routing in cluster-based wireless sensor network

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

Achieving the best quality as per user requirement is one of the important challenges in Wireless Sensor Network (WSN) containing numerous sensor nodes with limited battery power. The time-critical applications in WSN demand energy-efficient and reliable transmission of data with limited resource availability. To resolve these issues, our proposed optimal cluster head selection method choose node as CH subjected to minimal end-to-end delay and congestion index. The nodes with maximum remaining energy, not being subjected to delay and heavy traffic have been selected as a cluster head (CH) for the next round. The Inter-cluster routing path constructed based on energy, delay, and congestion index cost function to achieve aggregated bandwidth through the establishment of multipath. MQoScMR supports adaptive CH and path selection, tuning QoS parameter according to application requirement. The technique proposed outperforms when compared with the existing protocol in terms of minimized energy consumption, delay, packet drop ratio, and high throughput.

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

Similar content being viewed by others

References

  1. Ari AAA, Yenke BO, Labraoui N, Damakoa I, Gueroui A (2016) A power efficient cluster-based routing algorithm for wireless sensor networks: honeybees swarm intelligence based approach. J Netw Comput Appl 69:77–97

    Article  Google Scholar 

  2. Rhee CS (2016) An energy efficient routing algorithm based on clustering in wireless sensor network. Conver Sec J 16(2):3–9

    Google Scholar 

  3. Battula L, Raja PV (2016) Power efficient gathering in sensor information systems protocol using K-means clustering algorithm. Int J Sci Eng Comput Technol 6(4):133–137

    Google Scholar 

  4. Kumar D, Aseri TC, Patel RB (2009) EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks. Comput Commun 32(4):662–667

    Article  Google Scholar 

  5. Ma Z, Li G, Gong Q (2016) Improvement on leach-c protocol of wireless sensor network (leach-cc). Int J Future Gener Commun Netw 9(2):183–192

    Article  Google Scholar 

  6. Huynh TT, Dinh-Duc AV, Tran CH (2016) Delay-constrained energy-efficient cluster-based multi-hop routing in wireless sensor networks. J Commun Netw 18(4):580–588

    Article  Google Scholar 

  7. Sabet M, Naji HR (2015) A decentralized energy efficient hierarchical cluster-based routing algorithm for wireless sensor networks. AEU-Int J Electron Commun 69(5):790–799

    Article  Google Scholar 

  8. Batra PK, Kant K (2016) An improved cluster head selection algorithm using MAC layer information in wireless sensor network. Int J Sens Netw 22(2):75–86

    Article  Google Scholar 

  9. Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

  10. Sharma S, Jena SK (2011) A survey on secure hierarchical routing protocols in wireless sensor networks. In: Proceedings of the 2011 international conference on communication, computing and security. ACM, pp 146–151

  11. Younis O, Fahmy S (2004) HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 3(4):366–379

    Article  Google Scholar 

  12. Latiff NA, Tsimenidis CC, Sharif BS (2007) Energy-aware clustering for wireless sensor networks using particle swarm optimization. In: 2007 IEEE 18th international symposium on personal, indoor and mobile radio communication. IEEE, pp 1–5

  13. Arumugam GS, Ponnuchamy T (2015) EE-LEACH: development of energy-efficient LEACH Protocol for data gathering in WSN. EURASIP J Wirel Commun Netw 2015(1–9):76

    Article  Google Scholar 

  14. Huang J, Hong Y, Zhao Z, Yuan Y (2017) An energy-efficient multi-hop routing protocol based on grid clustering for wireless sensor networks. Clust Comput 20(4):3071–3083

    Article  Google Scholar 

  15. Kumar S, Ranjan P, Ramaswami R, Tripathy MR (2017) Resource efficient clustering and next hop knowledge based routing in multiple heterogeneous wireless sensor networks. Int J Grid High Perform Comput (IJGHPC) 9(2):1–20

    Article  Google Scholar 

  16. Haseeb K, Bakar KA, Abdullah AH, Darwish T (2017) Adaptive energy aware cluster-based routing protocol for wireless sensor networks. Wirel Netw 23(6):1953–1966

    Article  Google Scholar 

  17. Wang J, Cao J, Ji S, Park JH (2017) Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks. J Supercomput 73(7):3277–3290

    Article  Google Scholar 

  18. Agarkhed J, Patil YD (2019) Energy efficient service differentiated QoS aware routing in cluster-based wireless sensor network. Int J Hybrid Intell 1(1):79–95

    Article  Google Scholar 

  19. Peiravi A, Mashhadi HR, Hamed Javadi S (2013) An optimal energy-efficient clustering method in wireless sensor networks using multi-objective genetic algorithm. Int J Commun Syst 26(1):114–126

    Article  Google Scholar 

  20. Vijayalakshmi K, Anandan P (2018) A multi objective Tabu particle swarm optimization for effective cluster head selection in WSN. Clust Comput 1–8

  21. Raman CJ, James V (2018) FCC: fast congestion control scheme for wireless sensor networks using hybrid optimal routing algorithm. Clust Comput 1–11

  22. Selvakumar K, Arieth RM (2017) Contrast for QOS based clustered energy efficient protocol with PSO and multi-hop gateways in wireless sensor network. Clust Comput 1–8

  23. Adhikary DRD, Mallick DK (2017) A congestion aware, energy efficient, on demand fuzzy logic based clustering protocol for multi-hop wireless sensor networks. Wirel Pers Commun 97(1):1445–1474

    Article  Google Scholar 

  24. Jan MA, Jan SRU, Alam M, Akhunzada A, Rahman IU (2018) A comprehensive analysis of congestion control protocols in wireless sensor networks. Mobile Netw Appl 1–13

  25. Ahmed AM, Paulus R (2017) Congestion detection technique for multipath routing and load balancing in WSN. Wirel Netw 23(3):881–888

    Article  Google Scholar 

  26. Ben-Othman J, Yahya B (2010) Energy efficient and QoS based routing protocol for wireless sensor networks. J Parallel Distrib Comput 70(8):849–857

    Article  Google Scholar 

  27. Huang X, Fang Y (2008) Multiconstrained QoS multipath routing in wireless sensor networks. Wirel Netw 14(4):465–478

    Article  Google Scholar 

  28. Abazeed M, Faisal N, Zubair S, Ali A (2013) Routing protocols for wireless multimedia sensor network: a survey. J Sens 1–11

  29. Akkaya K, Younis M (2005) A survey on routing protocols for wireless sensor networks. Ad Hoc Netw 3(3):325–349

    Article  Google Scholar 

  30. Amgoth T, Jana PK (2015) Energy-aware routing algorithm for wireless sensor networks. Comput Electr Eng 41:357–367

    Article  Google Scholar 

  31. Raghunathan V, Schurgers C, Park S, Srivastava MB (2002) Energy-aware wireless microsensor networks. IEEE Signal Process Mag 19(2):40–50

    Article  Google Scholar 

  32. Malik K, Mittal AK, Gupta SK (1989) The k most vital arcs in the shortest path problem. Oper Res Lett 8(4):223–227

    Article  MathSciNet  Google Scholar 

  33. Zhong C, Malinen M, Miao D, Fränti P (2015) A fast minimum spanning tree algorithm based on K-means. Inf Sci 295:1–17

    Article  MathSciNet  Google Scholar 

  34. Agarkhed J, Dattatraya PY, Patil SR (2017) Performance evaluation of QoS-aware routing protocols in wireless sensor networks. In: Proceedings of the first international conference on computational intelligence and informatics. Springer, Singapore, pp 559–569

Download references

Author information

Authors and Affiliations

  1. Kalaburagi, India

    Jayashree Agarkhed, Patil Yogita Dattatraya & Siddrama Patil

Authors
  1. Jayashree Agarkhed
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Patil Yogita Dattatraya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siddrama Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Patil Yogita Dattatraya.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agarkhed, J., Dattatraya, P.Y. & Patil, S. Multi-QoS constraint multipath routing in cluster-based wireless sensor network. Int. j. inf. tecnol. 13, 865–876 (2021). https://doi.org/10.1007/s41870-020-00461-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-020-00461-5

Keywords

Search

Navigation