Skip to main content

Advertisement

SpringerLink
Log in

A novelistic approach for energy efficient routing using single and multiple data sinks in heterogeneous wireless sensor network

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

Abstract

In this paper, Improved Dual Hop Routing protocol (IDHR) and Multiple data sink-based Energy Efficient Cluster-based routing protocol (MEEC) are proposed. The Cluster Head (CH) selection in IDHR and MEEC is done by incorporating node density parameter along with other parameters, namely energy and distance between the node and the sink. In MEEC, multiple data sinks are employed to pact with the burden on the relaying nodes involved in data forwarding. The node density factor proves to be adherent for energy preservation of nodes by abating the average communication distance between the nodes and respective CH. The employment of multiple data sinks in MEEC avoids any dual hop communication between CHs and sink, which in turn alleviates hot-spot problem and ameliorates network longevity. As evident from the simulation results, IDHR and MEEC individually outperform competitive protocols, namely SEECP, DRESEP and TEDRP with respect to various performance metrics. Furthermore, the performance comparison of MEEC and IDHR is investigated to limelight the essence of employing multiple data sinks for a 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

Similar content being viewed by others

References

  1. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40:102–114

    Article  Google Scholar 

  2. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38:393–422

    Article  Google Scholar 

  3. Ortmann S, Langendoerfer P, Brzozowski M, Piotrowski K (2014) Wireless sensor networks: a key enabling Technology for Remote Healthcare. In: Systems Design for Remote Healthcare. Springer: 201–227

  4. Piotrowski K, Sojka A, Langendoerfer P (2010) Wireless sensor networks can save lives-benefits and open issues. Sensoren Messsyst 2010:24

    Google Scholar 

  5. Ammari HM, Gomes N, Grosky WI, et al (2012) Review of applications of wireless sensor networks. Wirel Sens Netw Curr Status Future Trends 1

  6. Abbasi AA, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30:2826–2841

    Article  Google Scholar 

  7. Soro S, Heinzelman WB (2009) Cluster head election techniques for coverage preservation in wireless sensor networks. Ad Hoc Netw 7:955–972

    Article  Google Scholar 

  8. Yarvis M, Kushalnagar N, Singh H, et al (2005) Exploiting heterogeneity in sensor networks. Proceedings of the 24th annual joint conference of the IEEE computer and communications societies, IEEE: 878–890

  9. Tanwar S, Kumar N, Rodrigues JJ (2015) A systematic review on heterogeneous routing protocols for wireless sensor network. J Netw Comput Appl 53:39–56

    Article  Google Scholar 

  10. Tao Y, Zhang Y, Ji Y (2013) Flow-balanced routing for multi-hop clustered wireless sensor networks. Ad Hoc Netw 11:541–554

    Article  Google Scholar 

  11. Li J, Mohapatra P (2007) Analytical modeling and mitigation techniques for the energy hole problem in sensor networks. Pervasive Mob Comput 3:233–254

    Article  Google Scholar 

  12. Mottola L, Picco GP (2011) MUSTER: adaptive energy-aware multisink routing in wireless sensor networks. IEEE Trans Mob Comput 10:1694–1709

    Article  Google Scholar 

  13. Liu T (2013) Avoiding energy holes to maximize network lifetime in gradient sinking sensor networks. Wirel Pers Commun 70:581–600

    Article  Google Scholar 

  14. Mohemed RE, Saleh AI, Abdelrazzak M, Samra AS (2017) Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks. Comput Netw 114:51–66

    Article  Google Scholar 

  15. Healy M, Newe T, Lewis E (2008) Wireless sensor node hardware: a review. Sensors, IEEE: 621–624

  16. Vieira MAM, Coelho CN, Da Silva DC, da Mata JM (2003) Survey on wireless sensor network devices. Proceedings of Conference on Emerging Technologies and Factory Automation, IEEE: 537–544

  17. Mittal N, Singh U (2015) Distance-based residual energy-efficient stable election protocol for WSNs. Arab J Sci Eng 40:1637–1646

    Article  Google Scholar 

  18. Mittal N, Singh U, Sohi BS (2017) A stable energy efficient clustering protocol for wireless sensor networks. Wirel Netw 23:1809–1821

    Article  Google Scholar 

  19. Mittal N, Singh U, Sohi BS (2017) A novel energy efficient stable clustering approach for wireless sensor networks. Wirel Pers Commun 95:2947–2971

    Article  Google Scholar 

  20. Liu X (2012) A survey on clustering routing protocols in wireless sensor networks. Sensors 12:11113–11153

    Article  Google Scholar 

  21. Xu Z, Chen L, Chen C, Guan X (2016) Joint clustering and routing design for reliable and efficient data collection in large-scale wireless sensor networks. IEEE Internet Things J 3:520–532

    Article  Google Scholar 

  22. Smaragdakis G, Matta I, Bestavros A (2004) SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. Boston University Computer Science Department

  23. Qing L, Zhu Q, Wang M (2006) Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Comput Commun 29:2230–2237

    Article  Google Scholar 

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

    Article  Google Scholar 

  25. Elbhiri B, Saadane R, Aboutajdine D, others (2010) Developed distributed energy-efficient clustering (DDEEC) for heterogeneous wireless sensor networks. Proceedings of 5th international symposium on I/V communications and Mobile network (ISVC), IEEE: 1–4

  26. Javaid N, Qureshi TN, Khan AH et al (2013) EDDEEC: enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks. Procedia Comput Sci 19:914–919

    Article  Google Scholar 

  27. Qureshi TN, Javaid N, Khan AH et al (2013) BEENISH: balanced energy efficient network integrated super heterogeneous protocol for wireless sensor networks. Procedia Comput Sci 19:920–925

    Article  Google Scholar 

  28. Kashaf A, Javaid N, Khan ZA, Khan IA (2012) TSEP: threshold-sensitive stable election protocol for WSNs. Proceedings of 10th International Conference on Frontiers of Information Technology (FIT), IEEE: 164–168

  29. Naranjo PGV, Shojafar M, Mostafaei H et al (2017) P-SEP: a prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks. J Supercomput 73:733–755

    Article  Google Scholar 

  30. Fersi G, Louati W, Jemaa MB (2016) CLEVER: cluster-based energy-aware virtual ring routing in randomly deployed wireless sensor networks. Peer--Peer Netw Appl 9:640–655

    Article  Google Scholar 

  31. Wu X, Chen G, Das SK (2008) Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE Trans Parallel Distrib Syst 19:710–720

    Article  Google Scholar 

  32. Liu A-F, Wu X-Y, Chen Z-G, Gui W-H (2010) Research on the energy hole problem based on unequal cluster-radius for wireless sensor networks. Comput Commun 33:302–321

    Article  Google Scholar 

  33. Liu A-F, Zhang P-H, Chen Z-G (2011) Theoretical analysis of the lifetime and energy hole in cluster based wireless sensor networks. J Parallel Distrib Comput 71:1327–1355

    Article  MATH  Google Scholar 

  34. Ren J, Zhang Y, Zhang K et al (2016) Lifetime and energy hole evolution analysis in data-gathering wireless sensor networks. IEEE Trans Ind Inform 12:788–800

    Article  Google Scholar 

  35. Gupta V, Pandey R (2016) An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks. Eng Sci Technol Int J 19:1050–1058

    Article  Google Scholar 

  36. Naureen A, Zhang N, Furber S (2017) Identifying energy holes in randomly deployed hierarchical wireless sensor networks. IEEE Access 5:21395–21418

    Article  Google Scholar 

  37. Akila IS, Venkatesan R (2018) An energy balanced geo-cluster head set based multi-hop routing for wireless sensor networks. Clust Comput 1–10

  38. Asharioun H, Asadollahi H, Wan T-C, Gharaei N (2015) A survey on analytical modeling and mitigation techniques for the energy hole problem in corona-based wireless sensor network. Wirel Pers Commun 81:161–187

    Article  Google Scholar 

  39. Liu A, Zhang D, Zhang P et al (2014) On mitigating hotspots to maximize network lifetime in multi-hop wireless sensor network with guaranteed transport delay and reliability. Peer--Peer Netw Appl 7:255–273

    Article  Google Scholar 

  40. Abdulla AE, Nishiyama H, Kato N (2012) Extending the lifetime of wireless sensor networks: a hybrid routing algorithm. Comput Commun 35:1056–1063

    Article  Google Scholar 

  41. Azad AP, Chockalingam A (2011) Enhancing lifetime of wireless sensor networks using multiple data sinks. Int J Sens Netw 9:139–157

    Article  Google Scholar 

  42. Cheng S-T, Chang T-Y (2012) An adaptive learning scheme for load balancing with zone partition in multi-sink wireless sensor network. Expert Syst Appl 39:9427–9434

    Article  Google Scholar 

  43. Kim D, Wang W, Wu W et al (2013) On bounding node--to--sink latency in wireless sensor networks with multiple sinks. Int J Sens Netw 13:13–29

    Article  Google Scholar 

  44. Safa H, Moussa M, Artail H (2014) An energy efficient genetic algorithm based approach for sensor-to-sink binding in multi-sink wireless sensor networks. Wirel Netw 20:177–196

    Article  Google Scholar 

  45. Jiang H, Sun R (2014) Energy optimized routing algorithm in multi-sink wireless sensor networks. Appl Math 8:349–354

    Google Scholar 

  46. Deng R, He S, Chen J (2018) An online algorithm for data collection by multiple sinks in wireless-sensor networks. IEEE Trans Control Netw Syst 5:93–104

    Article  MathSciNet  MATH  Google Scholar 

  47. Masdari M, Naghiloo F (2017) Fuzzy logic-based sink selection and load balancing in multi-sink wireless sensor networks. Wirel Pers Commun 97:2713–2739

    Article  Google Scholar 

  48. Cheng L, Niu J, Cao J et al (2014) QoS aware geographic opportunistic routing in wireless sensor networks. IEEE Trans Parallel Distrib Syst 25:1864–1875

    Article  Google Scholar 

  49. Ahmed A, Bakar KA, Channa MI et al (2017) Energy-aware and secure routing with trust for disaster response wireless sensor network. Peer--Peer Netw Appl 10:216–237

    Article  Google Scholar 

  50. Golsorkhtabar M, Nia FK, Hosseinzadeh M, Vejdanparast Y (2010) The novel energy adaptive protocol for heterogeneous wireless sensor networks. Proceedings of 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), IEEE: 178–182

  51. Chand S, Singh S, Kumar B (2014) Heterogeneous HEED protocol for wireless sensor networks. Wirel Pers Commun 77:2117–2139

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of ECE, Dr. B. R, Ambedkar National Institute of Technology, Jalandhar, 144011, India

    Sandeep Verma & Neetu Sood

  2. I. K. Gujral Punjab Technical University, Kapurthala, 110040, India

    Ajay Kumar Sharma

Authors
  1. Sandeep Verma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neetu Sood
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ajay Kumar Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sandeep Verma.

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

Verma, S., Sood, N. & Sharma, A.K. A novelistic approach for energy efficient routing using single and multiple data sinks in heterogeneous wireless sensor network. Peer-to-Peer Netw. Appl. 12, 1110–1136 (2019). https://doi.org/10.1007/s12083-019-00777-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-019-00777-5

Keywords

Search

Navigation