Analysis on energy consumption in smart grid WSN using path operator calculus centrality based HSA-PSO algorithm

Abstract

In this paper, the consumption of energy is efficiently balanced using the high searching capability of harmony search algorithm (HSA). However, centrality in finding the route is considered as an utmost challenge in finding the important node in WSN. Hence, the path operator calculus centrality (SPOCC) is used to optimize the centrality problems in routing. The SPOCC finds the main routing path using HSA, and high centrality node is estimated by particle swarm optimization (PSO) algorithm, thereby ensuring optimal routing with reduced energy consumption. The utilization of PSO improves the lifetime of nodes using its dynamic capability. The performance of the proposed hybrid algorithm is evaluated using the various result metrics in smart grid outdoor transmission environment. The results show that the proposed hybrid algorithm obtains better improvement in terms of reduced delay and high residual energy than the existing algorithms.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. Fadel E, Faheem M, Gungor VC, Nassef L, Akkari N, Malik MGA, Almasri S, Akyildiz IF (2017) Spectrum-aware bio-inspired routing in cognitive radio sensor networks for smart grid applications. Comput Commun 101:106–120

    Article  Google Scholar 

  2. Faheem M, Gungor VC (2017a) Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0. Appl Soft Comput 68:910–922

    Article  Google Scholar 

  3. Faheem M, Gungor VC (2017b) Capacity and spectrum-aware communication framework for wireless sensor network-based smart grid applications. Comput Stand Interfaces 53:48–58

    Article  Google Scholar 

  4. Faheem M, Gungor VC (2017c) MQRP: Mobile sinks-based QoS-aware data gathering protocol for wireless sensor networks-based smart grid applications in the context of industry 4.0-based on internet of things. Future Gen Comput Syst 82:358–374

    Article  Google Scholar 

  5. Faheem M, Abbas MZ, Tuna G, Gungor VC (2015) EDHRP: Energy efficient event driven hybrid routing protocol for densely deployed wireless sensor networks. J Netw Comput Appl 58:309–326

    Article  Google Scholar 

  6. Gungor VC, Lu B, Hancke GP (2010) Opportunities and challenges of wireless sensor networks in smart grid. IEEE Trans Ind Electron 57(10):3557–3564

    Article  Google Scholar 

  7. Li X, Tian YC, Ledwich G, Mishra Y, Han X, Zhou C (2018) Constrained optimization of multicast routing for wide area control of smart grid. IEEE Trans Smart Grid 10(4):3801–3808

    Article  Google Scholar 

  8. Nafi NS, Ahmed K, Gregory MA, Datta M (2018) Software defined neighborhood area network for smart grid applications. Future Gen Comput Syst 79:500–513

    Article  Google Scholar 

  9. Posada J, Toro C, Barandiaran I, Oyarzun D, Stricker D, de Amicis R, Pinto EB, Eisert P, Döllner J, Vallarino I (2015) Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE Comput Graph Appl 35(2):26–40

    Article  Google Scholar 

  10. Royer EM, Melliar-Smith PM, Moser LE (2001) An analysis of the optimum node density for ad hoc mobile networks. In: IEEE international conference on communications, 2001. ICC 2001, vol 3. IEEE, pp 857–861

  11. Sahin D, Gungor VC, Kocak T, Tuna G (2014) Quality-of-service differentiation in single-path and multi-path routing for wireless sensor network-based smart grid applications. Ad Hoc Netw 22:43–60

    Article  Google Scholar 

  12. Shah GA, Gungor VC, Akan OB (2013) A cross-layer QoS-aware communication framework in cognitive radio sensor networks for smart grid applications. IEEE Trans Ind Inf 9(3):1477–1485

    Article  Google Scholar 

  13. Syarif A, Abouaissa A, Idoumghar L, Lorenz P, Schott R, Staples GS (2016) New path centrality based on operator calculus approach for wireless sensor network deployment. IEEE Trans Emerg Top Comput 7(1):162–173

    Article  Google Scholar 

  14. Syarif A, Abouaissa A, Lorenz P (2017) Operator calculus approach for route optimizing and enhancing wireless sensor network. J Netw Comput Appl 97:1–10

    Article  Google Scholar 

  15. Wan J, Tang S, Shu Z, Li D, Wang S, Imran M, Vasilakos AV (2016) Software-defined industrial internet of things in the context of industry 4.0. IEEE Sensors J 16(20):7373–7380

    Article  Google Scholar 

  16. Wang Y, Deng Q, Liu G, Hao X, Song B (2016) An energy-efficient query based on variable region for large-scale smart grid. China Commun 13(10):119–136

    Article  Google Scholar 

  17. Wang H, Han G, Zhu C, Chan S, Zhang W (2017) TCSLP: a trace cost based source location privacy protection scheme in WSNs for smart cities. Future Gen Comput Syst (In Press, Corrected Proof)

  18. Wollschlaeger M, Sauter T, Jasperneite J (2017) The future of industrial communication: automation networks in the era of the internet of things and industry 4.0. IEEE Ind Electron Mag 11(1):17–27

    Article  Google Scholar 

  19. Yigit M, Incel OD, Gungor VC (2014) On the interdependency between multi-channel scheduling and tree-based routing for WSNs in smart grid environments. Comput Netw 65:1–20

    Article  Google Scholar 

  20. Yigit M, Gungor VC, Fadel E, Nassef L, Akkari N, Akyildiz IF (2016) Channel-aware routing and priority-aware multi-channel scheduling for WSN-based smart grid applications. J Netw Comput Appl 71:50–58

    Article  Google Scholar 

  21. Zhou Z, Du C, Shu L, Hancke G, Niu J, Ning H (2016) An energy-balanced heuristic for mobile sink scheduling in hybrid WSNs. IEEE Trans Ind Inf 12(1):28–40

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to R. Hemalatha.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Communicated by V. Loia.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hemalatha, R., Prakash, R. & Sivapragash, C. Analysis on energy consumption in smart grid WSN using path operator calculus centrality based HSA-PSO algorithm. Soft Comput 24, 10771–10783 (2020). https://doi.org/10.1007/s00500-019-04580-5

Download citation

Keywords

  • Path Operator Calculus Centrality
  • Harmonic Search Algorithm
  • Particle Swarm Optimization