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A Novel Technique for Gateway Selection in Hybrid MANET Using Genetic Algorithm

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Abstract

Integration of Mobile Ad hoc NETworks (MANETs) with the Internet has been paid immense attention in the field of heterogeneous networks. In MANET some intermediate nodes called Internet Gateways (IGs) are responsible for sending the data traffic of source nodes towards the fixed nodes in the Internet. The key issue considered while selecting IG nodes is its optimised throughput with the reduced delay in resource constraint mobile nodes. In this paper, a genetic algorithm inspired Delay Sensitive Gateway Selection (DSGS) scheme is proposed considering the issue of network delay by minimising the total distance travelled by the source nodes to the gateway. The performance of the proposed GA-based DSGS scheme is studied using a comparative approach. The simulation results demonstrate that the proposed scheme significantly outperforms the conventional schemes and is capable of achieving higher network throughput while minimising the end-to-end delay.

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All data generated or analysed during this study are included in this article.

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References

  1. Selvakumar, M., & Sudhakar, B. (2021). Energy efficient clustering with secure routing protocol using hybrid evolutionary algorithms for mobile Adhoc networks. Wireless Personal Communications, 13(12), 1828–1839.

    Google Scholar 

  2. Sharma, R. K., Sharma, A. K., & Jain, V. (2018). Genetic algorithm-based routing protocol for energy efficient routing in MANETs. In Next-Generation Networks, 638, 33–40.

    Article  Google Scholar 

  3. Naseem, M., & Kumar, C. (2017). Queue-based multiple path load balancing routing protocol for MANETs. International Journal of Communication Systems, 30(6), 31–41.

    Article  Google Scholar 

  4. Priya, J. S., Femina, M. A., & Samuel, R. A. (2020). APSO-MVS: An adaptive particle swarm optimization incorporating multiple velocity strategies for optimal leader selection in hybrid MANETs. Soft Computing, 24, 18349–18365.

    Article  Google Scholar 

  5. Usman, M., Jan, M. A., He, X., & Alam, M. (2018). Performance evaluation of high definition video streaming over mobile ad hoc networks. Signal Processing, 148, 303–313.

    Article  Google Scholar 

  6. Xu, H., Zhao, Y., Zhang, L., & Wang, J. (2019). A bio-inspired gateway selection scheme for hybrid mobile ad hoc networks. IEEE Access, 7, 61997–62010.

    Article  Google Scholar 

  7. Sharef, B., Alsaqour, R., Alawi, M., Abdelhaq, M., & Sundararajan, E. (2018). Robust and trust dynamic mobile gateway selection in heterogeneous VANET-UMTS network. Vehicular Communications, 12, 75–87.

    Article  Google Scholar 

  8. Hu, Z., Wen, X., Lu, Z., & Jing, W. (2017). AORS: Adaptive mobile data offloading based on attractor selection in heterogeneous wireless networks. Wireless Networks, 23(3), 831–842.

    Article  Google Scholar 

  9. Srivastava, P., & Kumar, R. (2018). An ANN based QoS aware adaptive gateway discovery approach for MANET and infrastructured networks integration. Adhoc and Sensor Wireless Networks, 41(3), 295–323.

    Google Scholar 

  10. Tian, D., Wei, J., Zhou, J., Sheng, Z., Chen, M., Ni, Q., & Leung, V. C. (2017). From cellular decision making to adaptive handoff in heterogeneous wireless networks. IEEE Wireless Communications Letters, 7(1), 2–5.

    Article  Google Scholar 

  11. Bozorgchenani, A., & Jahanshahi, M. (2017). A novel reliability and traffic aware gateway selection scheme in wireless mesh networks. Wireless Personal Communications, 96(4), 6111–6128.

    Article  Google Scholar 

  12. Muruganandam, S., & Renjit, J. A. (2021). Real-time reliable clustering and secure transmission scheme for QoS development in MANET. Peer-to-Peer Networking and Applications, 14(6), 3502–3517.

    Article  Google Scholar 

  13. Ahmad, M., Hameed, A., Ikram, A. A., & Wahid, I. (2019). State-of-the-art clustering schemes in mobile ad hoc networks: Objectives, challenges, and future directions. IEEE Access, 7, 17067–17081.

    Article  Google Scholar 

  14. Mohindra, A., & Gandhi, C. (2020). Weighted multipath energy-aware clustered stable routing protocol for mobile ad hoc networks. International Journal of Sensors Wireless Communications and Control, 10(3), 308–317.

    Article  Google Scholar 

  15. Saminathan, K., & Thangavel, R. (2022). Energy efficient and delay aware clustering in mobile adhoc network: A hybrid fruit fly optimization algorithm and whale optimization algorithm approach. Concurrency and Computation: Practice and Experience. https://doi.org/10.1002/cpe.6867

    Article  Google Scholar 

  16. Sharifi, S. A., & Babamir, S. M. (2020). The clustering algorithm for efficient energy management in mobile ad-hoc networks. Computer Networks, 166, 1069–1083.

    Article  Google Scholar 

  17. Hamamoto, A. H., Carvalho, L. F., Sampaio, L. D. H., Abrao, T., & Proenca, M. L., Jr. (2018). Network anomaly detection system using genetic algorithm and fuzzy logic. Expert Systems with Applications, 92, 390–402.

    Article  Google Scholar 

  18. Jha, S. K., & Eyong, E. M. (2018). An energy optimization in wireless sensor networks by using genetic algorithm. Telecommunication Systems, 67(1), 113–121.

    Article  Google Scholar 

  19. Yuan, X., Elhoseny, M., El-Minir, H. K., & Riad, A. M. (2017). A genetic algorithm-based, dynamic clustering method towards improved WSN longevity. Journal of Network and Systems Management, 25(1), 21–46.

    Article  Google Scholar 

  20. Prakash, B., Jayashri, S., & Karthik, T. S. (2019). A hybrid genetic artificial neural network (G-ANN) algorithm for optimization of energy component in a wireless mesh network toward green computing. Soft Computing, 23(8), 2789–2798.

    Article  Google Scholar 

  21. Prasad, A. Y., & Rayanki, B. (2019). A generic algorithmic protocol approaches to improve network life time and energy efficient using combined genetic algorithm with simulated annealing in MANET. International Journal of Intelligent Unmanned Systems, 8(1), 23–42.

    Article  Google Scholar 

  22. Bhardwaj, A., & El-Ocla, H. (2020). Multipath routing protocol using genetic algorithm in mobile ad hoc networks. IEEE Access, 8, 177534–177548.

    Article  Google Scholar 

  23. Zhang, Q., Ding, L., & Liao, Z. (2019). A novel genetic algorithm for stable multicast routing in mobile AD hoc networks. China Communications, 16(8), 24–37.

    Article  Google Scholar 

  24. Ahmad, M., Hameed, A., Ullah, F., Wahid, I., Rehman, S. U., & Khattak, H. A. (2020). A bio-inspired clustering in mobile adhoc networks for internet of things based on honey bee and genetic algorithm. Journal of Ambient Intelligence and Humanized Computing, 11(11), 4347–4361.

    Article  Google Scholar 

  25. Nabati, M., Maadani, M., & Pourmina, M. A. (2021). AGEN-AODV: An intelligent energy-aware routing protocol for heterogeneous mobile ad-hoc networks. Mobile Networks and Applications 1–12.

  26. Kushwah, R., Tapaswi, S., & Kumar, A. (2020). Multipath delay analysis using queuing theory for gateway selection in hybrid MANET. Wireless Personal Communications, 111(1), 9–32.

    Article  Google Scholar 

  27. Srivastava, P., & Kumar, R. (2018). A timestamp-based adaptive gateway discovery algorithm for ubiquitous internet access in MANET (pp. 153–162). In Next-generation networks: Springer.

  28. Kannan, K., Sivaranjani, P., Sathish Kumar, S., Nalini, M., Balaji, V. R., & Sanjeevi, P. (2021). SPAHN novel approach for PL-AG gateway discovery for internet connectivity. Peer-to-Peer Networking and Applications, 14(4), 2275–2284.

    Article  Google Scholar 

  29. Verma, P. (2019). A Secure Gateway Discovery Protocol Using Elliptic Curve Cryptography for Internet-Integrated MANET (pp. 181–210). IGI Global: In Cryptographic Security Solutions for the Internet of Things.

  30. Atheeq, C., & Rabbani, M. M. A. (2017). Mutually authenticated key agreement protocol based on chaos theory in integration of internet and MANET. International Journal of Computer Applications in Technology, 56(4), 309–318.

    Article  Google Scholar 

  31. Hamza, F., & Vigila, S. M. C. (2021). Cluster head selection algorithm for MANETs using hybrid particle swarm optimization-genetic algorithm. International Journal of Computer Networks and Applications, 8(2), 119–129.

    Article  Google Scholar 

  32. Preetha, V., & Chitra, K. (2018). ZBMRP: Zone based MANET routing protocol with genetic algorithm and security enhancement using neural network learning. International Journal of Network Security, 20(6), 1115–1124.

    Google Scholar 

  33. Rajadurai, S., Veerappan, J., & Ramasamy, K. (2017). Optimization of multicast ad hoc on-demand routing protocol based on genetic algorithm with backup paths in MANET. Wireless Personal Communications, 94(4), 2095–2124.

    Article  Google Scholar 

  34. Gurumoorthy, K. B., Gopinath, S., & Kumar, K. V. (2019). Ant colony optimization and genetic algorithm integrated load balancing approach for MANET. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(5), 399–405.

    Google Scholar 

  35. Singh, K., & Singh, K. (2018). Intrusion detection and recovery of MANET by using ACO algorithm and genetic algorithm (pp. 97–109). In Next-Generation Networks: Springer.

  36. Prakash, J., Kumar, R., & Saini, J. P. (2017). Path load balancing adaptive gateway discovery in MANET-internet integration using PSO. International Journal of Intelligent Engineering and System, 10(4), 235–244.

    Article  Google Scholar 

  37. Zaman, R. U., Shehnaz Begum, S., Khan, UrRahmanKhan K., & Venugopal Reddy, A. (2017). Efficient adaptive path load balanced gateway management strategies for integrating MANET and the Internet. International Journal of Wireless and Microwave Technologies (IJWMT), 7(2), 57–75.

    Article  Google Scholar 

  38. Al Mojamed, M. (2020). Integrating mobile ad hoc networks with the internet based on OLSR. Wireless Communications and Mobile Computing. https://doi.org/10.1155/2020/8810761

    Article  Google Scholar 

  39. Atheeq, C., & Rabbani, M. (2017). Secure intelligence algorithm for data transmission in integrated internet Manet. International Journal of Computer Science and Applications, 14(2), 142–163.

    Google Scholar 

  40. Choudhary, R., & Sharma, P. K. (2019). An efficient approach for power aware routing protocol for MANETs using genetic algorithm. In Emerging trends in expert applications and security (pp. 133-138). Springer.

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Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Jaypee Institute of Information Technology, Noida, India

    R. Kushwah

  2. ABV-Indian Institute of Information Technology and Management, Gwalior, India

    S. Tapaswi & A. Kumar

Authors
  1. R. Kushwah
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  2. S. Tapaswi
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  3. A. Kumar
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All authors contributed to the study conception and design

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Correspondence to R. Kushwah.

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Kushwah, R., Tapaswi, S. & Kumar, A. A Novel Technique for Gateway Selection in Hybrid MANET Using Genetic Algorithm. Wireless Pers Commun 126, 1273–1299 (2022). https://doi.org/10.1007/s11277-022-09791-y

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