Advertisement

Review of WSN and Its Quality of Service Parameters Using Nature-Inspired Algorithm

  • Cosmena MahapatraEmail author
  • Ashish Payal
  • Meenu Chopra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1059)

Abstract

Wireless sensor networks have become the focus of many recent researches focusing on topics like energy optimization, compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting and many more. The three major concern revolves around efficient energy usage, service quality and security management. To achieve success in these domains, it is imperative to have WSN optimization. Also, in applications like vehicular ad hoc networks and body area sensor networks, there can be conflict between these concerns and hence requires some trade-off. Because of these heavy energy expenditure and data processing needs, there is a requirement to review which WSN-based research has been done for optimizing the same through the use of bio-mimetic strategy-based optimization techniques which encompass numerous optimization algorithms. Thus, this paper reviews the various researches done to optimize quality of service parameters of wireless sensor networks and hence also aims to classify the challenges which are faced by these nature-inspired algorithms in WSN environment and thus identify future scope to consider a more comprehensive approach toward the subject matter.

Keywords

Wireless sensor networks Nature-inspired algorithms Challenges QoS Optimization 

Notes

Acknowledgements

Foremost, we would like to express our sincere gratitude to the Doctoral Research Committee of Guru Gobind Singh Indraprastha University (GGSIPU), New Delhi: Prof. Dr. Pravin Chandra, Prof. Dr. C. S. Rai, Prof. Dr. Amrinder Kaur, Prof. Dr. B. V. R. Reddy, Prof. Dr. Amit Prakash, Dr. Anurag Jain and Dr. Rahul Johari, for their encouragement, insightful comments, and hard questions. Our sincere thanks also goes to Vivekananda Institute of Professional Studies (VIPS) Respected Chairman sir Shri. Dr. S. C. Vats, Vice Chairman Shri. Suneet Vats, Shri. Vineet Vats and rest of VIPS management. We also wish to thank Dr. Ravish Saggar, Dr. Shubra Saggar, Dr. Ashish Khanna, Dr. Deepak Gupta for their constant motivation and moral support. This would be a right place to thank Dr. Tania Mahapatra for giving her invaluable time to help make this manuscript comprehendible. Last but not the least; we would like to thank our parents and God for supporting us throughout our life.

References

  1. 1.
    Gante D, Aslan M (2014) Smart wireless sensor network management based on software-defined networking. In: 27th biennial symposium on Communications (QBSC), pp 71–75Google Scholar
  2. 2.
    Moon Y, Lee J, Park S (2008) Node management and implementation. In: 10th international conference on advanced communication technology, IEEE, pp 1738–9445Google Scholar
  3. 3.
    Mahmood M, Seah W, Welch I (2015) Reliability in wireless sensor networks: a survey and challenges ahead. Comput Netw 79:166–187CrossRefGoogle Scholar
  4. 4.
    Choi Y, Hong YG (2016) Study on coupling of software-defined networking and wireless sensor networks. In: 8th international conference on ubiquitous and future networks (ICUFN), pp 900–902Google Scholar
  5. 5.
    Yamsanwar Y, Sutar S (2017) Performance analysis of wireless sensor networks for QoS. In: 2017 international conference on science, pp 120–123Google Scholar
  6. 6.
    Ezdiani S, Acharyya IS, Sivakumar S, Al-Anbuky A (2017) Wireless sensor network softwarization: towards WSN adaptive QoS. IEEE Internet Things JGoogle Scholar
  7. 7.
    Wang J (2014) Trust-based QoS routing algorithm for wireless sensor net-works. In: Wang H (ed) 26th Chinese control and decision conference (CCDC)Google Scholar
  8. 8.
    Akkaya K, Younis M (2005) Energy-aware and QoS routing in wireless sensor networks. Springer Cluster Comput J 8:179–188CrossRefGoogle Scholar
  9. 9.
    Torregozal JP (2006) Quality of service aware route discovery for wireless sensor networks. In: ICE-ICASE, Busan, pp 2153–2157Google Scholar
  10. 10.
    Ning GZ, Song Q, Zhang L (2016) A qos-oriented high-efficiency resource allocation scheme in wireless multimedia sensor networks. IEEE Sens JGoogle Scholar
  11. 11.
    Ehsan S, Hamdaoui B (2012) A survey on energy-efficient routing techniques with QoS assurances for wireless multimedia sensor networks. IEEE Commun Surv Tutorials 14(2):265–278CrossRefGoogle Scholar
  12. 12.
    Kapur R (2015) Review on nature inspired algorithms in cloud computing. In: Proc. of IEEE international conference on computing communication and automation (ICCCA-2015) School of Computer Science and Engineering Galgotias University Uttar Pradesh India, pp 15–16Google Scholar
  13. 13.
    Yang XS (2014) Nature-inspired optimization algorithms. Elsevier, AmsterdamzbMATHGoogle Scholar
  14. 14.
    Vikhar PA (2016) Evolutionary algorithms: a critical review and its future prospects. In: 2016 proc. of international conference on global trends in signal processing, information computing and communication, Dec, pp 22–24Google Scholar
  15. 15.
    Paul A, Paul AM, Ghosh K (2016) Communication con-verging towards adaptive intelligence: a survey in 2nd international conference on computational intelligence and networks (CINE), pp 3–12Google Scholar
  16. 16.
    Fei Z, Li B Shaoshi Yang, Chengwen Xing, Hongbin Chen, Lajos Hanzo (2017) A survey of multi-objective optimization in wireless sensor networks: metrics algorithms and open problems. Commun Surv Tu-torials IEEE 19(1):550–586CrossRefGoogle Scholar
  17. 17.
    Birattari DM (2010) Ant colony optimization. In: encyclopedia of machine learning, SpringerGoogle Scholar
  18. 18.
    Zhang WGW (2010) A comprehensive routing protocol in wireless sensor net-work based on ant colony algorithm. In: 2010 second international conference on networks security wireless communications and trusted computing (NSWCTC), vol 1, pp 41–44Google Scholar
  19. 19.
    Yang F (2010) An improved artificial immune algorithm. In: 6th international conference on natural computation, pp 2837–2841Google Scholar
  20. 20.
    Saleem K, Fisal N, Hafizah S, Kamilah S, Rashid R (2009) Ant based self-organized routing protocol for wireless sensor networks. Int J Commun Networks Inf Secur 1(2):42–46Google Scholar
  21. 21.
    Saleem, Caro, Farooq (2011) Swarm intelligence based routing protocol for wireless sensor networks: survey and future directions,. Inf Sci 181(20):4597–4624CrossRefGoogle Scholar
  22. 22.
    Aksa Benmohammed (2012) A comparison between geometric and bio-inspired algorithms for solving routing problem in wireless sensor net- work. Int J Networks Commun 2(3):27–32CrossRefGoogle Scholar
  23. 23.
    Hasan MZ, Wan TC (2013) Optimized quality of service for real-time wireless sensor networks using a partitioning multipath routing approach. J Comput Networks Commun 2013:1–18CrossRefGoogle Scholar
  24. 24.
    Abbasi M, Latiff Chizari H (2014) Bioinspired evolutionary algorithm based for improving network coverage in wireless sensor networks. Sci World J 2014:1–8Google Scholar
  25. 25.
    Deepa Visalakshi K (2016) A self-organized QoS-aware RED-ACO routing protocol for wireless sensor networks. Middle-East J Sci Res 24:224–230Google Scholar
  26. 26.
    Kaur M, Sohi (2018) Comparative analysis of bio inspired optimization techniques. In wireless sensor networks with GA-PSO Approach,. Indian J Sci Technol 11(4):1–10CrossRefGoogle Scholar
  27. 27.
    Royyan, Ramli, Lee, Kim (2018) Bio-inspired scheme for congestion control in wireless sensor networks. In: 2018 14th IEEE international workshop on factory communication systems (WFCS)Google Scholar
  28. 28.
    Saunhita S and Mini M (2018), Optimized relay nodes positioning to achieve full connectivity in wireless sensor networks, Springer Science, Wirel Pers Commun, Springer, pp-1521–2540Google Scholar
  29. 29.
    Yadav, Saneh and Phogat, Manu. (2017). Study of nature inspired algorithms. Int J Comput Trends Technol. 49. 100–105.  https://doi.org/10.14445/22312803/ijctt-v49p115CrossRefGoogle Scholar
  30. 30.
    DengYi Zhang and WenHai Li (2011). Research on quality of service in wireless sensor networks. In Software Engineering and Service ScienceGoogle Scholar
  31. 31.
    Oreku GS (2013) Reliability in WSN for security: mathematical approach. In: 2013 international conference on computer applications technology (ICCAT), pp 1–6Google Scholar
  32. 32.
    Polastre J, Hill J, Culler D (2004) Versatile low power media access for wireless sensor networks. In: Proc. ACM SenSys’ 04, pp 95–107Google Scholar
  33. 33.
    Ruan, Zhu, Chew (2017) Energy-aware approaches for energy harvesting pow-ered wireless sensor nodes. IEEE Sens J 17(7):2165–2173CrossRefGoogle Scholar
  34. 34.
    Zhi-jie Han (2014) A novel wireless sensor networks structure based on the SDN. Int J Distrib Sens Networks 2014(7):1–7. Article ID 874047Google Scholar
  35. 35.
    Distefano S (2012) Evaluating reliability of WSN with sleep/wake-up interfering nodes. Int J Syst Sci 44:10–1793zbMATHGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Cosmena Mahapatra
    • 1
    • 2
    Email author
  • Ashish Payal
    • 1
  • Meenu Chopra
    • 2
  1. 1.University School of Information, Communication & TechnologyGuru Gobind Singh Indraprastha UniversityNew DelhiIndia
  2. 2.Vivekananda Institute of Professional StudiesGuru Gobind Singh Indraprastha UniversityNew DelhiIndia

Personalised recommendations