Log in

Energy efficient CLB approach to find optimum modulation scheme in wireless rechargeable sensor networks

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

Abstract

There has been a lot of improvement in energy savings in wireless sensor networks (WSNs) resulting in increased lifespan of sensor nodes. Consequently, WSNs has gained its widespread use in various fields like medical services, security, home automation, environmental monitoring, and lot more. However, gaining successes leads to extensive acceptance of WSNs particularly at the places where human beings cannot reach. Being most acceptable, it still faces number of challenges like: battery constraint, low speed communication and harsh environment. Many researchers have come up with innovative ideas or energy management approaches to prolong the lifetime of hungry sensor nodes and to make the network more reliable and operational. In this paper, the CLB (Charging with Load Balancing) scheme is firstly proposed based on Laser power Beaming (LPB,) then it is implemented on various modulation schemes to test the optimum and robust modulation type for Wireless Rechargeable Sensor Networks (WRSNs).

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Angurala M et al. (2017) Evaluating Performance of Different Modulation Schemes on Modified Cooperative AODV. International Interdisciplinary Conference on Science Technology Engineering Management Pharmacy and Humanities Held on 22nd –23rd, in Singapore ISBN: 9780998900001

  2. Zhang Y et al (2018) An efficient EH-WSN energy management mechanism. Tsinghua Sci Technol 23(4):406–418

    Article  Google Scholar 

  3. Samuel KD et al (2011) Improving energy efficiency in wireless sensor network using mobile sink. Advances in networks and communications. CCSIT 2011. Commun Comput Inf Sci 132(1):63–69

    Google Scholar 

  4. Elshrkawey M et al (2017) An enhancement approach for reducing the energy consumption in wireless sensor networks. J King Saud Univ Comput Inf Sci 30(2):259–267

    Google Scholar 

  5. Quintero VL et al (2019) Improvements of energy-efficient techniques in WSNs: a MAC-protocol approach. IEEE Commun Surv Tutor 21(2):1188–1208

    Article  Google Scholar 

  6. Jang YJ et al (2011) An energy-efficient routing algorithm in wireless sensor networks. Future Gen Inf Technol 7105(1):183–189

    Google Scholar 

  7. Elrefaei JH et al (2019) Energy-efficient wireless sensor network for nuclear radiation detection. J Radiat Res Appl Sci 12(1):1–10

    Article  Google Scholar 

  8. Cardei M et al (2002) Wireless sensor networks with energy efficient organization. J Interconnect Netw 3(4):213–229

    Article  MathSciNet  Google Scholar 

  9. Angurala M et al (2018) Optimal topology in WSNs using energy enhanced technique. J Adv Res Dyn Control Syst 9(1):149–155

    Google Scholar 

  10. Angurala M et al (2020) Performance analysis of modified AODV routing protocol with lifetime extension of wireless sensor networks. IEEE Access 8(1):10606–10613

    Article  Google Scholar 

  11. Elsmany EFA et al (2019) EESRA: energy efficient scalable routing algorithm for wireless sensor networks. IEEE Access 7(1):96974–96983

    Article  Google Scholar 

  12. Li L, Li D (2018) An energy-balanced routing protocol for a wireless sensor network. J Sensors 1(1):1–13

    Google Scholar 

  13. Sangaiah AK (2019) Energy consumption in point-coverage wireless sensor networks via bat algorithm. IEEE Access 7(1):180258–180269

    Article  Google Scholar 

  14. Zhao M et al (2014) A framework of joint mobile energy replenishment and data gathering in wireless rechargeable sensor networks. IEEE Trans Mob Comput 13(12):2689–2705

    Article  Google Scholar 

  15. **e L et al (2012) Making sensor networks immortal: an energy-renewal approach with wireless power transfer IEEE/ACM trans. Networking 20(6):1748–1761

    Article  Google Scholar 

  16. Engmann F et al (2018) Prolonging the lifetime of wireless sensor networks: a review of current techniques. Wirel Commun Mobile Comput 1(1):1–24

    Article  Google Scholar 

  17. Zennaro N et al (2010) Planning and deploying long distance wireless sensor networks: the integration of simulation and experimentation. Ad-Hoc Mobile Wirel Netw 6288(1):191–210

    Article  Google Scholar 

  18. Amutha J et al (2019) WSN strategies based on sensors, deployment, sensing models, coverage and energy efficiency: review, approaches and open issues

  19. Sheik MD et al (2012) Energy efficient modulation techniques for fault tolerant two-tiered wireless sensor networks. J Asian Sci Res 2(3):124–131

    Google Scholar 

  20. Himanshu S et al (2012) Energy efficiency of the IEEE 802.15.4 standard in wireless sensor networks: modeling and improvement perspectives. Int J Comput Appl 58(9):12–19

    Google Scholar 

  21. Sanjeev K et al (2011) Bit error rate analysis of reed-solomon code for efficient communication system. Int J Comput Appl 30(12):11–15

    Google Scholar 

  22. Saurabh M, Singh G (2011) IReed-solomon code performance for M-ary modulation over AWGN channel. Int J Eng Sci Technol 3(5):3739–3745

    Google Scholar 

  23. **e L et al (2015) Multi-node wireless energy charging in sensor networks. IEEE Trans Netw 23(1):437–450

    Article  Google Scholar 

  24. Zeng Y et al (2017) Communications and signals design for wireless power transmission. IEEE Trans Commun 65(1):2264–2290

    Article  Google Scholar 

  25. Kurumbanshi S et al (2018) Increasing the lifespan of wireless adhoc network using probabilistic approaches: a survey. Int J Inf Technol 10(4):537–542

    Google Scholar 

  26. Agarkhed J et al (2020) Multi-QoS constraint multipath routing in cluster-based wireless sensor network. Int j inf tecnol. https://doi.org/10.1007/s41870-020-00461-5

    Article  Google Scholar 

  27. Asada G et al (1998) Wireless integrated network sensors: low power systems on a chip. In: European Solid State Circuits Conference 1998

  28. Chakrabarti A et al (2003) Using predictable observer mobility for power efficient design of sensor networks. In: Zhao F, Guibas LJ (eds) IPSN 2003. LNCS, vol. 2634, pp. 129–145. Springer, Heidelberg

  29. Zhang Z (2005) Energy efficient multi-hop polling in clusters of two-layered heterogeneous sensor networks. In: 19th IEEE international parallel and distributed processing symposium (IPDPS 2005)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohit Angurala.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Angurala, M., Bala, M. & Bamber, S.S. Energy efficient CLB approach to find optimum modulation scheme in wireless rechargeable sensor networks. Int. j. inf. tecnol. 13, 269–276 (2021). https://doi.org/10.1007/s41870-020-00561-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-020-00561-2

Keywords

Navigation