Advertisement

CUWSN: energy efficient routing protocol selection for cluster based underwater wireless sensor network

  • Kamalika BhattacharjyaEmail author
  • Sahabul Alam
  • Debashis De
Technical Paper
  • 6 Downloads

Abstract

Energy efficient routing protocol selection for Cluster based Underwater Wireless Sensor Network (CUWSN) is aimed to support monitoring and controlling underwater scenarios in the field of Internet of Underwater Things. The crucial requirement of Underwater Wireless Sensor Network (UWSN) is to prolong network lifespan. The aim of this article is to build energy-efficient UWSN that will trim energy expenditure as well as improve performance in the underwater scenario. In the proposed CUWSN, a UWSN architecture is designed, which uses the benefits of cluster head and multi-hop transmission. The proposed CUWSN extends the network lifetime by using multi-hop transmission. The proposed CUWSN model is simulated using QualNet 7.1 simulation tool. In this article, energy consumption, throughput, packet delivery ratio, transmission delay, error signals, and packet loss parameter indicators are considered to investigate the performance of proposed CUWSN. The outcomes of proposed CUWSN exhibit that the AODV routing protocol surpasses the DYMO routing protocol by 80%, the IERP routing protocol by 75%, STAR routing protocol by 47% and ZRP routing protocol by 81% in perspective of energy efficiency. In references to other performance indicators like average path loss and average interference the IERP routing protocol and in case of throughput the ZRP routing protocol performs well among the five routing protocols. Finally, the AODV routing protocol is energy conservative in the proposed CUWSN.

Notes

Acknowledgements

The authors are grateful to DST FIST SR/FST/ETI-296/2011 and UGC for Maulana Azad National Fellowship having with reference no. F1-F1.1/2013-14/MANF-2013-14-MUS-WES-22695 in order to successfully complete the present work.

References

  1. Agarwal R, Kumar S, Hegde RM (2015) Algorithms for crowd surveillance using passive acoustic sensors over multimodal sensor network. IEEE Sens J 15(3):1920–1930.  https://doi.org/10.1109/JSEN.2014.2369474 Google Scholar
  2. Ahmad I, Ashraf U, Ghafoor A (2016) A comparative QoS survey of mobile ad hoc network routing protocols. J Chin Inst Eng 39(5):585–592.  https://doi.org/10.1080/02533839.2016.1146088 Google Scholar
  3. Al-Dhief FT, Sabri N, Salim MS, Fouad S, Aljunid SA (2018) MANET routing protocols evaluation: AODV, DSR and DSDV perspective. In: EDP Sciences on MATEC web of conferences, vol 150, pp 1–6.  https://doi.org/10.1051/matecconf/201815006024
  4. Al Salti F, Alzeidi N, Arafeh BR (2017) EMGGR: an energy-efficient multipath grid-based geographic routing protocol for underwater wireless sensor networks. Wirel Netw 23(4):1301–1314.  https://doi.org/10.1007/s11276-016-1224-0 Google Scholar
  5. Alkindi Z, Alzeidi N, Touzene BAA (2018) Performance evolution of grid based routing protocol for underwater wireless sensor networks under different mobile models. Int J Wirel Mob Netw (IJWMN) 10(1):13–25Google Scholar
  6. Ayaz M, Baig I, Abdullah A, Faye I (2011) A survey on routing techniques in underwater wireless sensor networks. J Netw Comput Appl 34(6):1908–1927.  https://doi.org/10.1016/j.jnca.2011.06.009 Google Scholar
  7. Azam I, Javaid N, Ahmad A, Abdul W, Almogren A, Alamri A (2017) Balanced load distribution with energy hole avoidance in underwater WSNs. IEEE Access 5:15206–15221.  https://doi.org/10.1109/ACCESS.2017.2660767 Google Scholar
  8. Bhattacharjya K, Alam S, De D (2018a) Performance analysis of DYMO, ZRP and AODV routing protocols in a multi hop grid based underwater wireless sensor network. In: 2nd International conference on computational intelligence, communications and business analytics (CICBA). Springer Nature.  https://doi.org/10.1007/978-981-13-8578-0_37
  9. Bhattacharjya K, Alam S, De D (2018b) TTCBT: two tier complete binary tree based wireless sensor network for FSR and LANMAR routing protocols. Microsyst Technol.  https://doi.org/10.1007/s00542-018-3982-3 Google Scholar
  10. Chen H, Wu X, Liu G, Wang Y (2015) A novel multi-module separated linear UWSNs sensor node. IEEE Sens J 11(4):4119–4126.  https://doi.org/10.1109/JSEN.2015.2453409 Google Scholar
  11. Diamant R, Lampe L (2013) Underwater localization with time-synchronization and propagation speed uncertainties. IEEE Trans Mob Comput 12(7):1257–1269.  https://doi.org/10.1109/TMC.2012.100 Google Scholar
  12. Emokpae LE, DiBenedetto S, Potteiger B, Younis M (2014) UREAL: Underwater reflection-enabled acoustic-based localization. IEEE Sens J 14(11):3915–3925.  https://doi.org/10.1109/JSEN.2014.2357331 Google Scholar
  13. Erdem HE, Gungor VC (2017) Lifetime analysis of energy harvesting underwater wireless sensor nodes. In: IEEE signal processing and communications applications conference (SIU), pp 1–4.  https://doi.org/10.1109/siu.2017.7960419
  14. Fang S, Da Xu L, Zhu Y, Ahati J, Pei H, Yan J, Liu Z (2014) An integrated system for regional environmental monitoring and management based on internet of things. IEEE Trans Ind Inform 10(2):1596–1605.  https://doi.org/10.1109/TII.2014.2302638 Google Scholar
  15. Govindasamy J, Punniakody S (2017) A comparative study of reactive, proactive and hybrid routing protocol in wireless sensor network under wormhole attack. J Electr Syst Inf Technol 5(3):735–744.  https://doi.org/10.1016/j.jesit.2017.02.002 Google Scholar
  16. Han G, Jiang J, Shu L, Xu Y, Wang F (2012) Localization algorithms of underwater wireless sensor networks: a survey. Sensors 12(2):2026–2061.  https://doi.org/10.3390/s120202026 Google Scholar
  17. Han G, Jiang J, Shu L, Guizani M (2015) An attack-resistant trust model based on multidimensional trust metrics in underwater acoustic sensor network. IEEE Trans Mob Comput 14(12):2447–2459.  https://doi.org/10.1109/TMC.2015.2402120 Google Scholar
  18. He Y, Zhu L, Sun G, Qiao J (2018a) Cooperative localization and evaluation of small-scaled spherical underwater robots. Microsyst Technol.  https://doi.org/10.1007/s00542-018-4014-z Google Scholar
  19. He Y, Zhu L, Sun G, Qiao J, Guo S (2018b) Underwater motion characteristics evaluation of multi amphibious spherical robots. Microsyst Technol.  https://doi.org/10.1007/s00542-018-3986-z Google Scholar
  20. Jiang J, Han G, Guo H, Shu L, Rodrigues JJ (2016) Geographic multipath routing based on geospatial division in duty-cycled underwater wireless sensor networks. J Netw Comput Appl 59:4–13.  https://doi.org/10.1016/j.jnca.2015.01.005 Google Scholar
  21. Khan A, Ahmedy I, Anisi MH, Javaid N, Ali I, Khan N, Alsaqer M, Mahmood H (2018a) A localization-free interference and energy holes minimization routing for underwater wireless sensor networks. Sensors 18(1):165–182.  https://doi.org/10.3390/s18010165 Google Scholar
  22. Khan A, Ali I, Rahman AU, Imran M, Mahmood H (2018b) Co-EEORS: cooperative energy efficient optimal relay selection protocol for underwater wireless sensor networks. IEEE Access 6:28777–28789.  https://doi.org/10.1109/ACCESS.2018.2837108 Google Scholar
  23. Lee S, Kim D (2013) Underwater hybrid routing protocol for UWSNs. In: IEEE fifth international conference on ubiquitous and future networks (ICUFN), pp 472–475.  https://doi.org/10.1109/icufn.2013.6614865
  24. Li X, Zhao D (2017) Capacity research in cluster-based underwater wireless sensor networks based on stochastic geometry. China Commun 14(6):80–87.  https://doi.org/10.1109/CC.2017.7961365 Google Scholar
  25. Liang Q, Zhang B, Zhao C, Pi Y (2013) TDoA for passive localization: underwater versus terrestrial environment. IEEE Trans Parallel Distrib Syst 24(10):2100–2108.  https://doi.org/10.1109/TPDS.2012.310 Google Scholar
  26. Meratnia N, Havinga PJ, Casari P, Petrioli C, Grythe K, Husoy T, Zorzi M (2011) CLAM—Collaborative embedded networks for submarine surveillance: an overview. In: OCEANS 2011 IEEE-Spain, pp 1–4.  https://doi.org/10.1109/oceans-spain.2011.6003499
  27. Park MK, Rodoplu V (2007) UWAN-MAC: an energy-efficient MAC protocol for underwater acoustic wireless sensor networks. IEEE J Ocean Eng 32(3):710–720.  https://doi.org/10.1109/JOE.2007.899277 Google Scholar
  28. Patil MSA, Mishra MP (2017) Improved mobicast routing protocol to minimize energy consumption for underwater wireless sensor networks. Int J Res Sci Eng 3(2):197–204Google Scholar
  29. Rahman MA, Lee Y, Koo I (2017) EECOR: an energy-efficient cooperative opportunistic routing protocol for underwater acoustic sensor networks. IEEE Access 5:14119–14132.  https://doi.org/10.1109/ACCESS.2017.2730233 Google Scholar
  30. Rani S, Talwar R, Malhotra J, Ahmed SH, Sarkar M, Song H (2015) A novel scheme for an energy efficient Internet of Things based on wireless sensor networks. Sensors 15(11):28603–28626.  https://doi.org/10.3390/s151128603 Google Scholar
  31. Rani S, Ahmed SH, Malhotra J, Talwar R (2017) Energy efficient chain based routing protocol for underwater wireless sensor networks. J Netw Comput Appl 92:42–50.  https://doi.org/10.1016/j.jnca.2017.01.011 Google Scholar
  32. Saeed N, Celik A, Al-Naffouri T, Alouini MS (2018) Energy harvesting hybrid acoustic-optical underwater wireless sensor networks localization. Sensors 18(1):51–67.  https://doi.org/10.3390/s18010051 Google Scholar
  33. Saeed N, Celik A, Al-Naffouri TY, Alouini MS (2019) Localization of energy harvesting empowered underwater optical wireless sensor networks. IEEE Trans Wirel Commun 18(5):2652–2663.  https://doi.org/10.1109/TWC.2019.2906309 Google Scholar
  34. Teja GS, Samundiswary P (2014) Performance analysis of DYMO protocol for IEEE 802.15. 4 based WSNs with mobile nodes. In: IEEE computer communication and informatics (ICCCI), pp 1–5.  https://doi.org/10.1109/iccci.2014.6921821
  35. Van Glabbeek R, Höfner P, Portmann M, Tan WL (2016) Modelling and verifying the AODV routing protocol. Distrib Comput 29(4):279–315.  https://doi.org/10.1007/s00446-015-0262-7 MathSciNetzbMATHGoogle Scholar
  36. Varshney PK, Agrawal GS, Sharma SK (2016) Relative performance analysis of proactive routing protocols in wireless ad hoc networks using varying node density. Invertis J Sci Technol 9(3):161–169Google Scholar
  37. Wahid A, Lee S, Kim D (2014) A reliable and energy-efficient routing protocol for underwater wireless sensor networks. Int J Commun Syst 27(10):2048–2062.  https://doi.org/10.1002/dac.2455 Google Scholar
  38. Wan Z, Liu S, Ni W, Xu Z (2018) An energy-efficient multi-level adaptive clustering routing algorithm for underwater wireless sensor networks. Cluster Comput.  https://doi.org/10.1007/s10586-018-2376-8 Google Scholar
  39. Wang K, Gao H, Xu X, Jiang J, Yue D (2016) An energy-efficient reliable data transmission scheme for complex environmental monitoring in underwater acoustic sensor networks. IEEE Sens J 16(11):4051–4062.  https://doi.org/10.1109/JSEN.2015.2428712 Google Scholar
  40. Wang Z, Han G, Qin H, Zhang S, Sui Y (2018) An energy-aware and void-avoidable routing protocol for underwater sensor networks. IEEE Access 6:7792–7801.  https://doi.org/10.1109/ACCESS.2018.2805804 Google Scholar
  41. Wang S, Nguyen TL, Shin Y (2019) Energy-efficient clustering algorithm for magnetic induction-based underwater wireless sensor networks. IEEE Access 7:5975–5983.  https://doi.org/10.1109/ACCESS.2018.2889910 Google Scholar
  42. Yildiz HU (2019) Maximization of underwater sensor networks lifetime via fountain codes. IEEE Trans Ind Inform.  https://doi.org/10.1109/tii.2019.2892866 Google Scholar
  43. Yildiz HU, Gungor VC, Tavli B (2018) Packet size optimization for lifetime maximization in underwater acoustic sensor networks. IEEE Trans Ind Inform.  https://doi.org/10.1109/tii.2018.2841830 Google Scholar
  44. Yu Z, Xiao C, Zhou G (2014) Multi-objectivization-based localization of underwater sensors using magnetometers. IEEE Sens J 14(4):1099–1106.  https://doi.org/10.1109/JSEN.2013.2287915 Google Scholar
  45. Yuan F, Zhan Y, Wang Y (2014) Data density correlation degree clustering method for data aggregation in WSN. IEEE Sens J 14(4):1089–1098.  https://doi.org/10.1109/JSEN.2013.2293093 Google Scholar
  46. Zenia NZ, Aseeri M, Ahmed MR, Chowdhury ZI, Kaiser MS (2016) Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: a survey. J Netw Comput Appl 71:72–85.  https://doi.org/10.1016/j.jnca.2016.06.005 Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Kamalika Bhattacharjya
    • 1
    Email author
  • Sahabul Alam
    • 1
  • Debashis De
    • 1
  1. 1.Centre of Mobile Cloud Computing, Department of Computer Science and EngineeringMaulana Abul Kalam Azad University of Technology, West BengalHaringhata, NadiaIndia

Personalised recommendations