Journal of Soft Computing Paradigm
IRO Journals
Volume 1 — Issue 1 — September 2019

HYBRIDIZED GENETIC-SIMULATED ANNEALING ALGORITHM FOR PERFORMANCE OPTIMIZATION IN WIRELESS ADHOC NETWORK

https://doi.org/10.36548/jscp.2019.1.001
Jennifer S. Raj
Professor, Department of Electronics & Communication Engineering, Gnanamani College of Technology, Namakal
K. Rahimunnisa
Associate Professor,Department of ECE,Easwari Engineering College,Chennai, India
PDF
PDF

How to Cite

Raj, Jennifer S., and K. Rahimunnisa. 2019. “HYBRIDIZED GENETIC-SIMULATED ANNEALING ALGORITHM FOR PERFORMANCE OPTIMIZATION IN WIRELESS ADHOC NETWORK”. Journal of Soft Computing Paradigm 1 (1): 1-13. https://doi.org/10.36548/jscp.2019.1.001.
ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver AMA

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX

Keywords

— Wireless Adhoc network
— Multi-populated genetic algorithm
— Simulated annealing
— Shortest path
— Fuzzy classifier
— malicious activity
Published: 30-09-2019

Abstract

The wireless Adhoc network are framed instantaneously utilizing the neighboring available mobile nodes and are capable of reconfiguring and healing. This autonomous behavior of the WANET and their other unique characteristics such as high mobility, limited battery power and dynamic topology changes incorporates several challenges in routing process for the transmission of the information. The traditional methods did not shows improvement and the existing methods also resulted with moderate improvements in performance of the WANET. So the paper proposes a hybridized method for the routing process combining the multi-populated genetic with simulated annealing to identify the shortest path and the fuzzy logic in detection of the malicious activities enhancing the performance of the network preventing the packet losses. The proposed method is validated using the network simulator-2 and its performance is analyzed.

References

  1. Li, Kun, Liwei Jia, and Xiaoming Shi. "An Efficient Hybridized Genetic Algorithm." In 2018 IEEE International Conference of Safety Produce Informatization (IICSPI), pp. 118-121. IEEE, 2018.
  2. Srinivas, Mandavilli, and Lalit M. Patnaik. "Genetic algorithms: A survey." computer 27, no. 6 (1994): 17-26.
  3. Pathan, Al-Sakib Khan, ed. Security of self-organizing networks: MANET, WSN, WMN, VANET. CRC press, 2016.
  4. Conti, Marco, and Silvia Giordano. "Mobile ad hoc networking: milestones, challenges, and new research directions." IEEE Communications Magazine 52, no. 1 (2014): 85-96.
  5. Bheemalingaiah, M., M. M. Naidu, D. Sreenivasa Rao, and G. Varaprasad. "ENERGY AWARE NODE DISJOINT MULTIPATH ROUTING IN MOBILE AD HOC NETWORK." Journal of Theoretical & Applied Information Technology 5, no. 4 (2009).
  6. Tilwari, Valmik, Kaharudin Dimyati, M. H. D. Hindia, Anas Fattouh, and Iraj Sadegh Amiri. "Mobility, residual energy, and link quality aware multipath routing in MANETs with Q-learning algorithm." Applied Sciences 9, no. 8 (2019): 1582.
  7. Nayak, Padmalaya, and Anurag Devulapalli. "A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime." IEEE sensors journal 16, no. 1 (2015): 137-144.
  8. Yang, Shengxiang, Hui Cheng, and Fang Wang. "Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 40, no. 1 (2009): 52-63.
  9. Robinson, Y. Harold, and M. Rajaram. "Energy-aware multipath routing scheme based on particle swarm optimization in mobile ad hoc networks." The Scientific World Journal 2015 (2015).
  10. Kumar, Pravin, Sachin Tripathi, and Pankaj Pal. "Neural network based reliable transport layer protocol for MANET." In 2018 4th International Conference on Recent Advances in Information Technology (RAIT), pp. 1-6. IEEE, 2018.
  11. Xie, Tongyi, Jiawei Mo, and Baohua Huang. "A Secure AODV Protocol Improvement Scheme Based on Fuzzy Neural Network." In International Conference on Security and Privacy in Communication Systems, pp. 453-467. Springer, Cham, 2018.
  12. Labed, Said, Akram Kout, and Salim Chikhi. "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, no. 2 (2019): 131-151.
  13. Anand, M., and T. Sasikala. "Efficient energy optimization in mobile ad hoc network (MANET) using better-quality AODV protocol." Cluster Computing (2018): 1-7.
  14. Bisen, Dhananjay, and Sanjeev Sharma. "Fuzzy based detection of malicious activity for security assessment of MANET." National Academy science letters 41, no. 1 (2018): 23-28.
  15. Lanjewar, Priyanka D., and V. M. Thakare. "Performance and Optimization of MANET Routing Protocols." International Journal of Computer Applications 975 (2015): 8887.
  16. https://www.geeksforgeeks.org/introduction-of-mobile-ad-hoc-network-manet/