An Improved Location-Based Genetic Algorithm for Routing in FANETs

Amrita Yadav¹

Section:Research Paper, Product Type: Journal-Paper
Vol.11 , Issue.2 , pp.23-30, Apr-2023

Online published on Apr 30, 2023

Copyright © Amrita Yadav . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
This paper describes a genetic algorithm-based approach which uses location-based routing strategy for flying ad hoc networks (FANETs). The objective of this paper is to enhance transmission between the nodes in FANETs since routing is one of the primary issues in FANETs and see whether genetic algorithms can be a solution for this issue. Many routing protocols have been designed and implemented but there is no such efficient protocol designed yet which improves routing on all parameters. The paper also shows comparison between the standard genetic algorithm and proposed genetic algorithm. The considered parameters for comparison and testing are packet delivery rate, overhead, end-to-end delay, throughput and energy utilization. The outcomes demonstrate that the suggested method outperforms the current genetic algorithm.

Key-Words / Index Term :
UAV, Routing, protocol, FANET, genetic, location, energy, algorithm

References :
[1] Cumino, Pedro &Maciel, Kaled& Tavares, Thais & Oliveira, Helder May &Rosário, Denis &Cerqueira, Eduardo. “Cluster-Based Control Plane Messages Management in Software-Defined Flying Ad-Hoc Network”. Sensors. 20. 67. 10.3390/s20010067, 2019.
[2] Yanmaz, Evsen & Yahyanejad, Saeed &Rinner, Bernhard &Hellwagner, Hermann &Bettstetter, Christian. “Drone Networks: Communications, Coordination, and Sensing. Ad Hoc Networks”. 68. 10.1016/j.adhoc.2017.09.001, 2017.
[3] Bekan Kitaw, “Exploiting Packet Travel Time and Energy factor in delay sensitive application of MANET”, International Journal of Scientific Research in Computer Science and Engineering (IJSRCSE), , vol.9, Issue.4, pp.36-43, 2021.
[4] Hidehiko Okada, “Evolutionary Training of Binary Neural Networks by Genetic Algorithm”, International Journal of Scientific Research in Computer Science and Engineering (IJSRCSE), vol.9, Issue.6, pp.63-68, 2021.
[5] Jebari, Khalid, “Selection Methods for Genetic Algorithms”. International Journal of Emerging Sciences. 3. 333-344, 2013.
[6] Arpan Kumar Kar, “Bio inspired computing - A review of algorithms and scope of applications”. Expert Syst. Appl. 59, C, pp. 20–32. DOI:https://doi.org/10.1016/j.eswa.2016.04.018, 2016.
[7] Almufti, Saman &Marqas, Ridwan & Saeed, Vaman, “Taxonomy of bio-inspired optimization algorithms”, Journal of Advanced Computer Science & Technology. 8. 23. 10.14419/jacst.v8i2.29402,2019.
[8] Panchal, G., Panchal, D., & Patel, P. ,”Solving NP hard Problems using Genetic Algorithm”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (2) , 2015, 1824-1827, 2015.
[9] Kim, Kyung-Joong& Cho, Sung-Bae, “Evolutionary Algorithms for Board Game Players with Domain Knowledge” 10.1007/978-3-540-72705-7_4, 2007.
[10] Carretero, Javier & Xhafa, Fatos, “Use of genetic algorithms for scheduling jobs in large scale grid applications”, Technological and Economic Development of Economy - TECHNOL ECON DEV ECON. 12. 11-17. 10.1080/13928619.2006.9637716, 2006.
[11] Bader, Ehab & H. O. Nasereddin, Hebah, “Using Genetic Algorithm in Network Security”. International Journal of Research and Reviews in Applied Sciences. 5. 148-154, 2019.
[12] Al-Ghazal, Mustafa & El-Sayed, Ayman &Kelash, Hamedy, “ Routing Optimization using Genetic Algorithm in Ad Hoc Networks” 497 - 503. 10.1109/ISSPIT.2007.4458010, 2007.
[13] Nagib, Gihan., “Optimal Routing In Ad-Hoc Network Using Genetic Algorithm” Int. J. Advanced Networking and Applications. 3. 1323-1328,2012.
[14] Abdullah, Nibras & Al-wesabi, Ola &Baklizi, Mahmoud &Ramadass, Sureswaran. “Multi-constrained routing using genetic algorithm”, IEEE International Conference on RFID-Technologies and Applications, RFID-TA 2013. 10.1109/RFID-TA.2013.6694537, 2013.
[15] Hampiholi, Aishwarya & Kumar, Vijaya. , “ Efficient routing protocol in IoT using modified Genetic algorithm and its comparison with existing protocols”. 1-5. 10.1109/CIMCA.2018.8739759, 2018.
[16] J. Seetaram and P. S. Kumar, "An energy aware Genetic Algorithm Multipath Distance Vector Protocol for efficient routing," International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India, pp. 1975-1980, doi: 10.1109/WiSPNET.2016.7566488, 2016.
[17] D. Pal, D. Shah and S. K. Bhagat, "Design of a Genetic Algorithm Based Shortest Path Routing with different Mutation Techniques," 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), Coimbatore, India, 2019, pp. 1-5, doi: 10.1109/ICECCT.2019.8869243.
[18] Chinnasamy, Rajan&Moorthi, Shanthi. , “ Genetic based optimization for multicast routing algorithm for MANET”. Sadhana. 40. 2341-2352. 10.1007/s12046-015-0437-8, 2016.
[19] Hassan, Mustafa &Muniyandi, Ravie. “An improved hybrid technique for energy and delay routing in mobile ad-hoc networks”. 12. 134-139,2017.
[20] Singh, Kuldeep & Verma, Anil. “ A Trust Model for Effective Cooperation in Flying Ad Hoc Networks Using Genetic Algorithm”. 10.1109/ICCSP.2018.8524558, 2017.
[21] Zhang, Guoan& Wu, Min & Duan, Wei & Huang, Xinming, “Genetic Algorithm Based QoS Perception Routing Protocol for VANETs”, Wireless Communications and Mobile Computing. 2018. 1-10. 10.1155/2018/3897857, 2019.
[22] Sun, Xiuqiao& Wang, Jian & Wu, Weitiao& Liu, Wenjia. “Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol” Sustainability. 10. 4120. 10.3390/su10114120, 2019.
[23] Delima, AllemarJhone&Sison, Ariel & Medina, Ruji., “A modified genetic algorithm with a new crossover mating scheme”. 7. 165-181. 10.11591/ijeei.v7i2.1047, 2019.
[24] Trivedi, V., & Nayak, P., “Modified AODV Using Genetic Algorithm to Minimize Energy Consumption in MANET”, 2019.
[25] Liu, Jianqiang&Huo, Shuai & Wang, Yi, “Throughput optimization for flying ad hoc network based on position control using genetic algorithm”, International Journal of Metrology and Quality Engineering. 11. 11. 10.1051/ijmqe/2020012, 2020.
[26] Muruganantham, Naveen & El-Ocla, Hosam, “Routing Using Genetic Algorithm in a Wireless Sensor Network”, Wireless Personal Communications. 111. 10.1007/s11277-019-07011-8, 2022.
[27] Wei, Xing & Yang, Hua & Huang, Wentao, “A Genetic-Algorithm-Based Optimization Routing for FANETs”, Frontiers in Neurorobotics. 15. 697624. 10.3389/fnbot.2021.697624, 2021.
[28] Uçan, Ferhat &Altilar, D. Turgay, “Using Genetic Algorithms for Navigation Planning in Dynamic Environments”. Applied Computational Intelligence and Soft Computing. 2012. 10.1155/2012/560184, 2012.
[29] Sajid, Mohammad & Mittal, Himanshu & Pare, Shreya & Prasad, Mukesh, “Routing and scheduling optimization for UAV assisted delivery system: A hybrid approach”, Applied Soft Computing. 126. 109225. 10.1016/j.asoc.2022.109225, 2022.
[30] Zhang, Jiankang& Liu, Dong & Chen, Sheng & Ng, Soon & Maunder, Robert &Hanzo, L., “Multiple-Objective Packet Routing Optimization for Aeronautical ad-hoc Networks”. IEEE Transactions on Vehicular Technology.2022.
[31] Venkataraman, Rishi &Muralirajan, Praveenraj&Devu, Pranith& Prasad, R &Kirthiga, S. “Energy Efficient Clustering and Routing Using GA-EAMMH”. 603-608. 10.1109/ICCES54183.2022.9835936, 2022.
[32] Xin, Wang &Cuiran, Li & Jianli, Xie, “ Research on Clustering Routing Protocol for Energy-Harvesting WSN”. 1460-1464. 10.1109/ICETCI55101.2022.9832077, 2022.
[33] Han, Youjia& Hu, Huangshui& Guo, Yuxin, “Energy-Aware and Trust-Based Secure Routing Protocol for Wireless Sensor Networks Using Adaptive Genetic Algorithm”. IEEE Access. pp. 1-1. 10.1109/ACCESS.2022.3144015, 2022.