Skip to main content
SpringerLink
Log in

Optimal route maintenance based on adaptive equilibrium optimization and GTA based route discovery model in MANET

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

Recently, routing is considered the main problem in MANET due to its dynamic nature. The route discovery and the optimal route selection from the multiple routes are established for the efficient routing in MANET. The major objective of this research is to select the optimal route for packet transmission in MANET. In this paper, four stages namely trust evaluation, route discovery, optmal route selection and route maintanance are elucidated. Initially, the trust evaluation is made by using ANFIS where the primary trust values are evaluated. The next stage is the route discovery scheme, in which the routes are established by Group teaching optimization algorithm (GTA). From the route discovery scheme, multiple routes are found. The optimal route for the transmission is selected with the help of the Adaptive equilibrium optimizer (AO) algorithm. Finally, the route maintenance process is established; if any of the routes fails for the broadcast it immediately selects the alternate optimal route from the multi-zone routing table for efficient packet transmission. The proposed approach is evaluated by various performance measures like throughput, energy consumption, packet delivery ratio, end-to-end delay, packet loss rate, detection rate, and routing overhead. This result describes that the proposed approach outperforms other state-of-art 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
Fig. 11

Similar content being viewed by others

References

  1. Velagaleti SB, GNITS S, Seetha M, Raju SV (2020 Feb) A novel method for trust evaluation in a mobile Ad Hoc network. Int J Comput Sci Inform Secur (IJCSIS) 18(2)

  2. Santhosh RM (May 2019) Securing public key infrastructure based manets by using efficient trust computation. Int Res J Eng Technol (IRJET) 06(05)

  3. Srinadh NR, Satyanarayana B (2019) Power-aware secure routing protocol in MANET based on reputation model and optimization. Int J Appl Eng Res 14(11):2704–2716

    Google Scholar 

  4. Anjali P, Kallada JJ (May 2019) Fitness function as trust value using to efficient multipath routing for mobile Ad Hoc network. Int Res J Eng Technol (IRJET) 06(05)

  5. Sathyaraj P, Devi DR (2020) Designing the routing protocol with secured IoT devices and QoS over Manet using trust-based performance evaluation method. J Ambient Intell Humaniz Comput:1–9

  6. Kausar Fatima S, Gauhar Fatima S, Abdul Sattar S, Srinivasa Rao DD (2019) A security scheme based on trust attack in manet. Int J Adv Res Eng Technol 10(2)

  7. Ananthakumaran S, Sathishkumar M, Bhavani R, Reddy RR (2020) Prevention of routing attacks using trust-based multipath protocol. Int J 9(3)

  8. Ponguwala M, Rao DS (2019) Secure group based routing and flawless trust formulation in MANET using unsupervised machine learning approach for IoT applications. EAI Endorsed Transactions on Energy Web 6(24)

  9. Yang H (2020) A study on improving secure routing performance using trust model in MANET. Mob Inf Syst 2020:1–17

    Google Scholar 

  10. Lwin MT, Yim J, Ko YB (2020) Blockchain-based lightweight trust management in mobile ad-hoc networks. Sensors. 20(3):698

    Article  Google Scholar 

  11. Nandgave-Usturge S (2020) Water spider monkey optimization algorithm for trust-based MANET secure routing in IoT. Int J Scientific Res Eng Trends 6(2):980–984

    Google Scholar 

  12. Mukhedkar MM, Kolekar U (2019) Trust-based secure routing in mobile ad hoc network using hybrid optimization algorithm. Comput J 62(10):1528–1545

    Article  MathSciNet  Google Scholar 

  13. Sun Z, Wei M, Zhang Z, Qu G (2019) Secure routing protocol based on multi-objective ant-colony-optimization for wireless sensor networks. Appl Soft Comput 77:366–375

    Article  Google Scholar 

  14. Mukhedkar MM, Kolekar U (2020) E-TDGO: an encrypted trust-based dolphin glowworm optimization for secure routing in mobile ad hoc network. Int J Commun Syst 33(7):e4252

    Article  Google Scholar 

  15. Kanagasundaram H, Ayyaswamy K (2019) Multi objective ALO based energy efficient and secure routing OLSR protocol in MANET. Int J Intell Eng Syst 12(1):74–83

    Google Scholar 

  16. Alkhamisi AO, Buhari SM, Tsaramirsis G, Basheri M (2020) An integrated incentive and trust-based optimal path identification in ad hoc on-demand multipath distance vector routing for MANET. Int J Grid Utility Computg 11(2):169–184

    Article  Google Scholar 

  17. Mariadas AE, Madhanmohan R (2020) Hybrid PSO-DE algorithm-based trust and congestion aware cluster routing algorithm for MANET. Int J Cloud Comput 9(2–3):330–354

    Article  Google Scholar 

  18. Keum D, Lim J, Ko YB (2020) Trust based multipath QoS routing protocol for Mission-critical data transmission in tactical ad-hoc networks. Sensors. 20(11):3330

    Article  Google Scholar 

  19. Kumar R, Shekhar S (2020) Trust-based fuzzy bat optimization algorithm for attack detection in manet. InSmart Innovations in Communication and Computational Sciences. pp. 3–12. Springer, Singapore

  20. Merlin RT, Ravi R (2019) Novel trust based energy aware routing mechanism for mitigation of black hole attacks in MANET. Wirel Pers Commun 104(4):1599–1636

    Article  Google Scholar 

  21. Zhang M, Yang M, Wu Q, Zheng R, Zhu J (2018) Smart perception and autonomic optimization: a novel bio-inspired hybrid routing protocol for MANETs. Futur Gener Comput Syst 81:505–513

    Article  Google Scholar 

  22. Yi JH, Deb S, Dong J, Alavi AH, Wang GG (2018) An improved NSGA-III algorithm with adaptive mutation operator for big data optimization problems. Futur Gener Comput Syst 88:571–585

    Article  Google Scholar 

  23. Buragohain M, Mahanta C (2008) A novel approach for ANFIS modeling based on full factorial design. Appl Soft Comput 8:609–625

    Article  Google Scholar 

  24. Zhang Y, Jin Z (2020) Group teaching optimization algorithm: a novel metaheuristic method for solving global optimization problems. Expert Syst Appl 148(113246):113246

    Article  Google Scholar 

  25. Rao RV, Savsani VJ, Vakharia DP (2012) Teaching–learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf Sci 183(1):1–15

    Article  MathSciNet  Google Scholar 

  26. Wunnava A, Naik MK, Panda R, Jena B, Abraham A (2020) A novel interdependence based multilevel thresholding technique using adaptive equilibrium optimizer. Eng Appl Artif Intell 94:103836

    Article  Google Scholar 

  27. Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S (2020) Equilibrium optimizer: a novel optimization algorithm. Knowl-Based Syst 191(105190):105190

    Article  Google Scholar 

  28. da Costa Bento CR, Wille EC (2020) Bio-inspired routing algorithm for MANETs based on fungi networks. Ad Hoc Netw:102248

  29. Labed S, Kout A, Chikhi S (2019) A new approach based bee colony for the resolution of routing problem in mobile ad-hoc networks. International Journal of Applied Metaheuristic Computing (IJAMC) 10(2):131–151

    Article  Google Scholar 

  30. Shende DK, Sonavane SS (2020) CrowWhale-ETR: CrowWhale optimization algorithm for energy and trust aware multicast routing in WSN for IoT applications. Wirel Netw:1–9

  31. Çaydaş U, Hasçalık A, Ekici S (2009) An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM. Expert Syst Appl 36(3):6135–6139

    Article  Google Scholar 

  32. Jayalakshmi P, Saravanan R (2020) ACO-based enhanced energy-efficient intelligent routing protocol for MANET. International Journal of Grid and Utility Computing 11(4):435–442

    Article  Google Scholar 

  33. Mohammed Najm Abdulredha, Bara'a A. Attea, Adnan Jumaa Jabir (2020) Heuristic and meta-heuristic optimization models for task scheduling in cloud-fog systems: a review. Iraqi Journal for Electrical and Electronic Engineering 16(2)

  34. Jiang F, Dashtipour K Hussain A (2019) August. A survey on deep learning for the routing layer of computer network. In 2019 UK/China Emerging Technologies (UCET). (pp. 1-4). IEEE

  35. Zhao H, Sun D, Yue H, Zhao M, Cheng S (2018) Dynamic trust model for vehicular cyber-physical systems. IJ Network Security 20(1):157–167

    Google Scholar 

  36. Zhao H, Yue H, Gu T et al (2019) CPS-based reliability enhancement mechanism for vehicular emergency warning system. Int J Intell Transp Syst Res 17(3):1–10

    Google Scholar 

  37. Sun D, Zhao H, Cheng S (2016) A novel membership cloud model-based trust evaluation model for vehicular ad hoc network of T-CPS[J]. Secur Commun Netw 9(18):5710–5723

    Article  Google Scholar 

  38. Zhao H, Chen Q, Shi W, Gu T, Li W (2019) Stability analysis of an improved car-following model accounting for the driver’s characteristics and automation. Physica A Statis Mech Appl 526(120990):120990

    Article  MathSciNet  Google Scholar 

  39. 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

  40. Jothi S, Chandrasekar A (2020) Genetic spider monkey-based routing protocol to increase the lifetime of the network and energy management in WSN. Int J Commun Syst 33(14):e4525

  41. Haseena KS, Anees S, Madheswari N (2014) Power optimization using EPAR protocol in MANET. Int J Innov Sci Eng Technol 1(6)

  42. Nisha S, Madheswari AN (2016) Secured authentication for internet voting in corporate companies to prevent phishing attacks. International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) 22(1):45–49

  43. Jose J, Gautam N, Tiwari M, Tiwari T, Suresh A, Sundararaj V, Rejeesh MR (2021) An image quality enhancement scheme employing adolescent identity search algorithm in the NSST domain for multimodal medical image fusion. Biomed Signal Process Control 66:102480

  44. Zhao H, Yue H, Tianlong GU, Li C, Zhou D (2021) Low delay and seamless connectivity-based message propagation mechanism for VANET of VCPS. Wireless Personal Communications. pp. 1–18

  45. Gowthul Alam MM, Baulkani S (2017) Reformulated query-based document retrieval using optimised kernel fuzzy clustering algorithm. Int J Bus Intell Data Min 12(3):299

    Google Scholar 

  46. Sundararaj V (2016) An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. Int J Intell Eng Syst 9(3):117–126

    Google Scholar 

  47. Gowthul Alam MM, Baulkani S (2019a) Geometric structure information based multi-objective function to increase fuzzy clustering performance with artificial and real-life data. Soft Comput 23(4):1079–1098

    Article  Google Scholar 

  48. Sundararaj V (2019) Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction. Int J Biomed Eng Technol 31(4):325

    Article  Google Scholar 

  49. Gowthul Alam MM, Baulkani S (2019b) Local and global characteristics-based kernel hybridization to increase optimal support vector machine performance for stock market prediction. Knowl Inf Syst 60(2):971–1000

    Article  Google Scholar 

  50. Hassan BA, Rashid TA (2020) Datasets on statistical analysis and performance evaluation of backtracking search optimisation algorithm compared with its counterpart algorithms. Data in Brief 28:105046

    Article  Google Scholar 

  51. Hassan BA (2020) CSCF: a chaotic sine cosine firefly algorithm for practical application problems. Neural Comput & Applic:1–20

  52. Rejeesh MR (2019) Interest point based face recognition using adaptive neuro fuzzy inference system. Multimed Tools Appl 78(16):22691–22710

    Article  Google Scholar 

  53. Sundararaj V, Muthukumar S, Kumar RS (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Comput Secur 77:277–288

    Article  Google Scholar 

  54. Sundararaj V, Anoop V, Dixit P, Arjaria A, Chourasia U, Bhambri P, Rejeesh MR, Sundararaj R (2020) CCGPA-MPPT: Cauchy preferential crossover-based global pollination algorithm for MPPT in photovoltaic system. Prog Photovolt Res Appl 28(11):1128–1145

    Article  Google Scholar 

  55. Vinu S (2019) Optimal task assignment in mobile cloud computing by queue based ant-bee algorithm. Wirel Pers Commun 104(1):173–197

    Article  Google Scholar 

  56. Gupta S, Deep K, Mirjalili S (2020) An efficient equilibrium optimizer with mutation strategy for numerical optimization. Appl Soft Comput 96:106542

Download references

Author information

Authors and Affiliations

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

    R. Hemalatha

  2. Loyola Institute of Technology, Kuthambakkam, 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

Corresponding author

Correspondence to R. Hemalatha.

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. Optimal route maintenance based on adaptive equilibrium optimization and GTA based route discovery model in MANET. Peer-to-Peer Netw. Appl. 14, 3416–3430 (2021). https://doi.org/10.1007/s12083-021-01186-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-021-01186-3

Keywords

Search

Navigation