Skip to main content
SpringerLink
Log in

LF Distribution and Equilibrium Optimizer Based Fuzzy Logic for Multipath Routing in MANET

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In the mobile ad hoc network (MANET), the optimal route recognition is considered to be the major issue in the multipath routing technique. Selecting a multipath is also considered as one of the challenging tasks to enhance the network lifetime. The routing protocol imagines several parameters such as enlarged power, link failures, obstacles, and topological changes during the exploration of the optimal route. In this, the optimal loop-free route is established by Equilibrium optimizer (EO) with fuzzy logic and this assures developing continuity. In the proposed algorithm, five phases are elucidated; route exploration, route maintenance, route recovery, reactive path setup and multipath routing setup phase. Initially, in the route exploration phase the equilibrium optimizer algorithm with fuzzy logic is used to establish the optimal routing for the packet transmission. For the appropriate node selection for routing, levy flight distribution mechanism is used in this paper. In the route maintenance phase, compute the status of the node prior to the data transmission. In the route recovery phase or the backward process, the backward reply from the destination is created. In the fourth phase, reactive path setup process is utilized. Finally in the multipath process, the multipath setup process is utilized for the header by the intermediate node. The proposed approach is evaluated by some of the performance measures such as throughput, energy consumption, end-to-end delay, packet delivery ratio, routing overhead and optimal path. This results describes that the proposed approach outperforms other existing approaches.

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

Similar content being viewed by others

Availability of data and material

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

References

  1. Iqbal Z, Khan S, Mehmood A, Lloret J, & Alrajeh NA., 2016. Adaptive cross-layer multipath routing protocol for mobile ad hoc networks. Journal of Sensors. 2016 May.

  2. Chander D, & Kumar R. 2017. Analysis of scalable and energy aware multicast routing protocols for MANETs. Indian J. Comput. Sci. Eng.(IJCSE).8(3).

  3. Shailaja P, & Rao C.G., 2020. Zone assisted mobility aware multipath routing (ZM2R) for energy constrained MANETs. Materials Today: Proceedings.

  4. Smail, O., Cousin, B., & Snoussaoui, I. (2017). Energy-aware and stable cluster-based multipath routing protocol for wireless ad hoc networks. International Journal of Networking and Virtual Organisations., 17(2–3), 229–51

    Article  Google Scholar 

  5. Abdali, T. A., Hassan, R., Muniyandi, R. C., Mohd Aman, A. H., Nguyen, Q., & N., Al-Khaleefa A.S. . (2020). Optimized particle swarm optimization algorithm for the realization of an enhanced energy-aware location-aided routing protocol in MANET. Information, 11(11), 529

    Article  Google Scholar 

  6. Sahu, R., Sharma, S., & Rizvi, M. A. (2020). ZBLE: Zone based efficient energy multipath protocol for routing in mobile Ad Hoc networks. Wireless Personal Communications, 15, 1–9

    Google Scholar 

  7. Olaniyan, O. M., Omodunbi, B. A., Adebimpe, E., Bolanle, W. W., Oyedepo, O. M., & Adanigbo, O. O. (2020). Power aware and secured routing protocol in mobile Ad-Hoc network: . A Survey Technology, 11(7), 706–17

    Google Scholar 

  8. Sridevi, U., Komarapalayam, N., & Kamaraj, K. (2020). An Efficient caching mechanism with optimized economic utility-aware enhanced reliable opportunistic routing protocol for enhancement on storage space utilization in MANETs. International Journal of Innovative Science and Research Technology, 5(10).

  9. Udaycharan, N., & Kumar, S. P. (2019). Fitness function based multipath routing protocol for energy efficient mobile Ad Hoc network. Journal of Engineering services, 10, 944–950

    Google Scholar 

  10. Sathish, V., & Thiyagarasu, D. (2016). Enhanced mac with delay aware multipath routing (EMAC–DAMR) mechanism for quality of service in mobile Ad Hoc networks. Journal of Theoretical and Applied Information Technology., 96(19), 12–21

    Google Scholar 

  11. Jayavenkatesan, R., & Mariappan, A. (2017). Energy efficient multipath routing for MANET based on hybrid ACO-FDRPSO. International Journal of Pure and Applied Mathematics., 115(6), 185–91

    Google Scholar 

  12. Abdali, T. A., Hassan, R., Muniyandi, R. C., Mohd Aman, A. H., Nguyen, Q. N., & Al-Khaleefa, A. S. (2020). Optimized particle swarm optimization algorithm for the realization of an enhanced energy-aware location-aided routing protocol in MANET. Information, 11(11), 529

    Article  Google Scholar 

  13. Merlin, R. T., & Ravi, R. (2019). Novel trust based energy aware routing mechanism for mitigation of black hole attacks in MANET. Wireless Personal Communications, 104(4), 1599–636

    Article  Google Scholar 

  14. Rahim R, Murugan S, Priya S, Magesh S, & Manikandan R. (2020). Taylor Based Grey Wolf Optimization Algorithm (TGWOA) For Energy Aware Secure Routing Protocol, International Journal of Computer Networks and Applications (IJCNA), vol. 7.

  15. Jayaramu, A. B., & Banga, M. K. (2020). Delay aware routing protocol using optimized AODV with BBO for MPLS-MANET. International Journal of Intelligent Engineering and Systems, 13(5), 29–37

    Article  Google Scholar 

  16. Kukreja, D., Sharma, D. K., Dhurandher, S. K., & Reddy, B. R. (2019). GASER: genetic algorithm-based secure and energy aware routing protocol for sparse mobile ad hoc networks. International Journal of Advanced Intelligence Paradigms, 13(1–2), 230–59

    Article  Google Scholar 

  17. Jubair, M. A., Mostafa, S. A., Muniyandi, R. C., Mahdin, H., Mustapha, A., Hassan, M. H., Mahmoud, M. A., Al-Jawhar, Y. A., Al-Khaleefa, A. S., & Mahmood, A. J. (2019). Bat optimized link state routing protocol for energy-aware mobile ad-hoc networks. Symmetry, 11(11), 1409

    Article  Google Scholar 

  18. Robinson, Y. H., Balaji, S., & Julie, E. G. (2019). PSOBLAP: Particle swarm optimization-based bandwidth and link availability prediction algorithm for multipath routing in mobile ad hoc networks. Wireless Personal Communications, 106(4), 2261–89

    Article  Google Scholar 

  19. Kukreja, D., & Sharma, D. K. (2019). T-SEA: trust based secure and energy aware routing protocol for mobile ad hoc networks. International Journal of Information Technology., 18, 1–5

    Google Scholar 

  20. Faramarzi, A., Heidarinejad, M., Stephens, B., & Mirjalili, S. (2020). Equilibrium optimizer: A novel optimization algorithm. Knowledge-Based Systems., 191, 105190

    Article  Google Scholar 

  21. Khan N.R., Sharma S, & Patheja P.S., (2018). Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization (EMPSO). International Research Journal of Engineering and Technology.5(1).

  22. Tilwari, V., Maheswar, R., Jayarajan, P., Sundararajan, T. V., Hindia, M. N., Dimyati, K., Ojukwu, H., & Amiri, I. S. (2020). MCLMR: A multicriteria based multipath routing in the mobile ad hoc networks. Wireless Personal Communications, 112(4), 2461–2483

    Article  Google Scholar 

  23. Houssein, E. H., Saad, M. R., Hashim, F. A., Shaban, H., & Hassaballah, M. (2020). Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems. Engineering Applications of Artificial Intelligence., 94, 103731

    Article  Google Scholar 

  24. Yang X.S., Cui Z., Xiao R., Gandomi A.H., & Karamanoglu M., (2013) May 16. editors. Swarm intelligence and bio-inspired computation: theory and applications. Newnes.

  25. Sundararaj, Vinu, Muthukumar, Selvi, & Kumar, R. S. (2018). An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Computers & Security, 77, 277–288

    Article  Google Scholar 

  26. Ravikumar, S. and Kavitha, D., 2020. IoT based home monitoring system with secure data storage by Keccak–Chaotic sequence in cloud server. Journal of Ambient Intelligence and Humanized Computing, pp.1-13.

  27. Sundararaj, V. (2017). Optimized denoising scheme via opposition based self-adaptive learning PSO algorithm for wavelet based ECG signal noise reduction. International Journal of Biomedical Engineering and Technology, 1(1), 1

    Article  Google Scholar 

  28. Rejeesh, M. R. (2019). Interest point based face recognition using adaptive neuro fuzzy inference system. Multimedia Tools and Applications, 78(16), 22691–22710

    Article  Google Scholar 

  29. Sundararaj, V. (2016). An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. International Journal of Intelligent Engineering and Systems, 9(3), 117–126

    Article  Google Scholar 

  30. Vinu, S. (2019). Optimal task assignment in mobile cloud computing by queue based ant-bee algorithm. Wireless Personal Communications, 104(1), 173–197

    Article  Google Scholar 

  31. Rejeesh, M. R., & Thejaswini, P. (2020). MOTF: Multi-objective optimal trilateral filtering based partial moving frame algorithm for image denoising. Multimedia Tools and Applications, 79(37), 28411–28430

    Article  Google Scholar 

  32. Sundararaj, V., Anoop, V., Dixit, P., Arjaria, A., Chourasia, U., Bhambri, P., & MR, R. and Sundararaj, R. . (2020). CCGPA-MPPT: Cauchy preferential crossover-based global pollination algorithm for MPPT in photovoltaic system. Progress in Photovoltaics: Research and Applications, 28(11), 1128–1145

    Article  Google Scholar 

  33. Jose, J., Gautam, N., Tiwari, M., Tiwari, T., Suresh, A., Sundararaj, V., & Rejeesh, M. R. (2021). An image quality enhancement scheme employing adolescent identity search algorithm in the NSST domain for multimodal medical image fusion. Biomedical Signal Processing and Control, 66, 102480

    Article  Google Scholar 

  34. Kavitha, D., & Ravikumar, S. (2021). IOT and context-aware learning-based optimal neural network model for real-time health monitoring. Transactions on Emerging Telecommunications Technologies, 32(1), e4132

    Article  Google Scholar 

  35. Kavitha, D., & Ravikumar, S. (2015). A Survey of different software Security attacks and risk analysis based on security threats. International Journal of Innovative Research in Computer and Communication Engineering, 3, 3452–3458

    Google Scholar 

  36. Gupta, S., Deep, K., & Mirjalili, S. (2020). An efficient equilibrium optimizer with mutation strategy for numerical optimization. Applied Soft Computing, 96, 106542

    Article  Google Scholar 

  37. Jothi, S., & Chandrasekar, A. (2020). Nelder mead based spider monkey optimization for optimal power and channel allocation in MANET. Journal of Circuits, Systems and Computers.

  38. Soundaram, J., & Arumugam, C. (2020) Genetic spider monkey-based routing protocol to increase the lifetime of the network and energy management in WSN. International Journal of Communication Systems, 33(14), e4525.

    Article  Google Scholar 

  39. Bala, K., Jothi, S., & Chandrasekar, A. (2019) An enhanced intrusion detection system for mobile ad-hoc network based on traffic analysis. Cluster Computing, 22(S6), 15205–15212.

    Article  Google Scholar 

  40. Hassan, B. A. & Rashid, T. A. (2021). A multidisciplinary ensemble algorithm for clustering heterogeneous datasets. Neural Computing and Applications, 1–24.

  41. Hassan, B. A. (2020). CSCF: A chaotic sine cosine firefly algorithm for practical application problems. Neural Computing and Applications, 1–20.

Download references

Funding

Not applicable

Author information

Authors and Affiliations

  1. St. Joseph’s College of Engineering, Chennai, India

    R. Hemalatha

  2. Loyola Institute of Technology, Chennai, India

    R. Umamaheswari

  3. Department of Computer Science and Engineering, St. Joseph’s college of Engineering, Chennai, India

    S. Jothi

Authors
  1. R. Hemalatha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Umamaheswari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Jothi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

RH agreed on the content of the study. RH,RU and SJ collected all the data for analysis. RH agreed on themethodology. RH,RU and SJ completed the analysis based on agreed steps. Results and conclusions arediscussed and written together. The author read and approved the final manuscript.

Corresponding author

Correspondence to R. Hemalatha.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Human and Animal Rights

This article does not contain any studies with human or animal subjects performed by any of the authors.

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.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hemalatha, R., Umamaheswari, R. & Jothi, S. LF Distribution and Equilibrium Optimizer Based Fuzzy Logic for Multipath Routing in MANET. Wireless Pers Commun 120, 1837–1861 (2021). https://doi.org/10.1007/s11277-021-08537-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08537-6

Keywords

Search

Navigation