Bio-inspired Routing Algorithms for UAV-based Networks: A Survey
DOI:
https://doi.org/10.26636/jtit.2025.3.2101Keywords:
bio-inspired routing protocols, FANET, routing protocols in FANETs, UAVAbstract
Rapid technological advancements, exponential growth, and unique characteristics are the key factors that enhance the usefulness of unmanned aerial vehicles (UAVs) in diverse applications, including military, agricultural, commercial, and communications-related fields. The use of UAVs for communication is a recent development that has become a topic of significant interest shown by researchers. A flying ad hoc network (FANET) made up of numerous UAVs cannot be developed without implementing an effective cooperative networking model that enables secure information sharing between UAVs. To achieve reliable and robust communication using FANETs, various design- and routing-related issues must be addressed in an appropriate manner. The use of bio-inspired algorithms for data routing in FANETs may be a promising direction, due to their ability to communicate efficiently in a swarm of devices. This work explores various bio-inspired routing algorithms proposed for transmitting data in UAV-based networks. Furthermore, their performance is evaluated and compared using routing metrics. All unresolved research concerns and prospective study avenues are examined based on the outcomes of the investigation conducted.
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[1] H. Zhao, H. Wang, W. Wu, and J. Wei, "Deployment Algorithms for UAV Airborne Networks Toward On-demand Coverage", IEEE Journal on Selected Areas in Communications, vol. 36, no. 9, pp. 2015-2031, 2018. DOI: https://doi.org/10.1109/JSAC.2018.2864376
View in Google Scholar
[2] J. Kwak, J.H. Park, and Y. Sung, "Emerging ICT UAV Applications and Services: Design of Surveillance UAVs", International Journal of Communication Systems, vol. 34, no. 2, article no. e4023, 2021. DOI: https://doi.org/10.1002/dac.4023
View in Google Scholar
[3] S.-Y. Park, C.S. Shin, D. Jeong, and H. Lee, "DroneNetX: Network Reconstruction Through Connectivity Probing and Relay Deployment by Multiple UAVs in Ad Hoc Networks", IEEE Transactions on Vehicular Technology, vol. 67, no. 11, pp. 11192-11207, 2018. DOI: https://doi.org/10.1109/TVT.2018.2870397
View in Google Scholar
[4] L. Ferranti, L. Bonati, S. D’Oro, and T. Melodia, "SkyCell: A Prototyping Platform for 5G Aerial Base Stations", 2020 IEEE 21st International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), Cork, Ireland, 2020. DOI: https://doi.org/10.1109/WoWMoM49955.2020.00062
View in Google Scholar
[5] I.U. Khan et al., "Smart IoT Control-based Nature Inspired Energy Efficient Routing Protocol for Flying Ad Hoc Network (FANET)", IEEE Access, vol. 8, pp. 56371-56378, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2981531
View in Google Scholar
[6] J. Zhang, J. Yan, and P. Zhang, "Multi-UAV Formation Control Based on a Novel Back-stepping Approach", IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 2437-2448, 2020. DOI: https://doi.org/10.1109/TVT.2020.2964847
View in Google Scholar
[7] A. Srivastava and J. Prakash, "Future FANET with Application and Enabling Techniques: Anatomization and Sustainability Issues", Computer Science Review, vol. 39, art. no. 100359, 2021. DOI: https://doi.org/10.1016/j.cosrev.2020.100359
View in Google Scholar
[8] G. Skorobogatov, C. Barrado, and E. Salamí, "Multiple UAV Systems: A Survey", Unmanned Systems, vol. 8, no. 02, pp. 149-169, 2020. DOI: https://doi.org/10.1142/S2301385020500090
View in Google Scholar
[9] I. Valiulahi and C. Masouros, "Multi-UAV Deployment for Throughput Maximization in the Presence of Co-channel Interference", IEEE Internet of Things Journal, vol. 8, no. 5, pp. 3605-3618, 2020. DOI: https://doi.org/10.1109/JIOT.2020.3023010
View in Google Scholar
[10] A. Pandey, P.K. Shukla, and R. Agrawal, "An Adaptive Flying Ad-hoc Network (FANET) for Disaster Response Operations to Improve Quality of Service (QoS)", Modern Physics Letters B, vol. 34, no. 10, art. no. 2050010, 2020. DOI: https://doi.org/10.1142/S0217984920500104
View in Google Scholar
[11] M.A. Al-Absi, A.A. Al-Absi, M. Sain, and H. Lee, "Moving Ad Hoc Networks - A Comparative Study", Sustainability, vol. 13, no. 11, article no. 6187, 2021. DOI: https://doi.org/10.3390/su13116187
View in Google Scholar
[12] Y. Cheriguene et al., "COCOMA: a Resource-optimized Cooperative UAVs Communication Protocol for Surveillance and Monitoring Applications", Wireless Networks, pp. 4429-4445, 2022. DOI: https://doi.org/10.1007/s11276-022-03031-8
View in Google Scholar
[13] X. Zhu, F. Vanegas, and F. Gonzalez, "An Approach for Multi-UAV System Navigation and Target Finding in Cluttered Environments", 2020 International Conference on Unmanned Aircraft Systems (ICUAS), Athens, Greece, pp. 1113-1120, 2020. DOI: https://doi.org/10.1109/ICUAS48674.2020.9214062
View in Google Scholar
[14] A. Guillen-Perez, A.-M. Montoya, J.-C. Sanchez-Aarnoutse, and M.-D. Cano, "A Comparative Performance Evaluation of Routing Protocols for Flying Ad-hoc Networks in Real Conditions", Applied Sciences., vol. 11, no. 10, art. no. 4363, 2021. DOI: https://doi.org/10.3390/app11104363
View in Google Scholar
[15] M. Nemati et al., "Non-terrestrial Networks with UAVs: A Projection on Flying Ad-hoc Networks", Drones, vol. 6, no. 11, art. no. 334, 2022. DOI: https://doi.org/10.3390/drones6110334
View in Google Scholar
[16] G. Amponis et al., "A Survey on FANET Routing from a Cross-layer Design Perspective", Journal of Systems Architecture, vol. 120, p. 102281, 2021. DOI: https://doi.org/10.1016/j.sysarc.2021.102281
View in Google Scholar
[17] A.H. Sawalmeh and N.S. Othman, "An Overview of Collision Avoidance Approaches and Network Architecture of Unmanned Aerial Vehicles (UAVs)", International Journal of Engineering and Technology, vol. 7, 2018,. DOI: https://doi.org/10.14419/ijet.v7i4.35.27395
View in Google Scholar
[18] S. Bitam, A. Mellouk, and S. Zeadally, "Bio-inspired Routing Algorithms Survey for Vehicular Ad Hoc Networks", IEEE Communications Surveys & Tutorials, vol. 17, no. 2, pp. 843-867, 2014. DOI: https://doi.org/10.1109/COMST.2014.2371828
View in Google Scholar
[19] Y. Zeng, R. Zhang, and T.J. Lim, "Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges", IEEE Communications Magazine, vol. 54, no. 5, pp. 36-42, 2016. DOI: https://doi.org/10.1109/MCOM.2016.7470933
View in Google Scholar
[20] A.V. Leonov, "Applying Bio-inspired Algorithms to Routing Problem Solution in FANET", Bulletin of the South Ural State University. Series Computer Technologies, Automatic Control, Radio Electronics, vol. 17, no. 2, pp. 5-23, 2017. DOI: https://doi.org/10.14529/ctcr170201
View in Google Scholar
[21] M.F. Khan, K.-L.A. Yau, R.M. Noor, and M. A. Imran, "Routing Schemes in FANETs: A Survey", Sensors, vol. 20, no. 1, art. no. 38, 2020. DOI: https://doi.org/10.3390/s20010038
View in Google Scholar
[22] T.R. Beegum, M.Y.I. Idris, M.N.B. Ayub, and H.A. Shehadeh, "Optimized Routing of UAVs Using Bio-inspired Algorithm in FANET: A Systematic Review", IEEE Access, vol. 11, pp. 15588-15622, 2023. DOI: https://doi.org/10.1109/ACCESS.2023.3244067
View in Google Scholar
[23] M.J. Almansor et al., "Routing Protocols Strategies for Flying Ad-hoc Network (FANET): Review, Taxonomy, and Open Research Issues", Alexandria Engineering Journal., vol. 109, pp. 553-577, 2024. DOI: https://doi.org/10.1016/j.aej.2024.09.032
View in Google Scholar
[24] N. Kumar, D. Puthal, T. Theocharides, and S.P. Mohanty, "Unmanned Aerial Vehicles in Consumer Applications: New Applications in Current and Future Smart Environments", IEEE Consumer Electronics Magazine, vol. 8, no. 3, pp. 66-67, 2019. DOI: https://doi.org/10.1109/MCE.2019.2892278
View in Google Scholar
[25] A. Orsino et al., "Effects of Heterogeneous Mobility on D2D- and Drone-assisted Mission-critical MTC in 5G", IEEE Communications Magazine, vol. 55, no. 2, pp. 79-87, 2017. DOI: https://doi.org/10.1109/MCOM.2017.1600443CM
View in Google Scholar
[26] A.A. Khuwaja et al., "A Survey of Channel Modeling for UAV Communications", IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 2804-2821, 2018. DOI: https://doi.org/10.1109/COMST.2018.2856587
View in Google Scholar
[27] N.K. Tomar et al., "FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation", IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 11, pp. 9375-9388, 2022. DOI: https://doi.org/10.1109/TNNLS.2022.3159394
View in Google Scholar
[28] N.H. Motlagh, T. Taleb, and O. Arouk, "Low-altitude Unmanned Aerial Vehicles-based Internet of Things Services: Comprehensive Survey and Future Perspectives", IEEE Internet of Things Journal, vol. 3, no. 6, pp. 899-922, 2016. DOI: https://doi.org/10.1109/JIOT.2016.2612119
View in Google Scholar
[29] M. Bacco et al., "Reliable M2M/IoT Data Delivery from FANETs via Satellite", International Journal of Satellite Communications and Networking, vol. 37, no. 4, pp. 331-342, 2019. DOI: https://doi.org/10.1002/sat.1274
View in Google Scholar
[30] G. Sun, D. Qin, T. Lan, and L. Ma, "Research on Clustering Routing Protocol Based on Improved PSO in FANET", IEEE Sensors Journal, vol. 21, no. 23, pp. 27168-27185, 2021. DOI: https://doi.org/10.1109/JSEN.2021.3117496
View in Google Scholar
[31] G.A. Kakamoukas, P.G. Sarigiannidis, and A.A. Economides, "FANETs in Agriculture - A Routing Protocol Survey", Internet Things, vol. 18, art. no. 100183, 2022. DOI: https://doi.org/10.1016/j.iot.2020.100183
View in Google Scholar
[32] L. Gupta, R. Jain, and G. Vaszkun, "Survey of Important Issues in UAV Communication Networks", IEEE Communications Surveys & Tutorials, vol. 18, no. 2, pp. 1123-1152, 2015. DOI: https://doi.org/10.1109/COMST.2015.2495297
View in Google Scholar
[33] X. Li and J. Yan, "LEPR: Link Stability Estimation-based Preemptive Routing protocol for Flying Ad Hoc Networks", 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, Greece, 2017.
View in Google Scholar
[34] J. Agrawal, M. Kapoor, and R. Tomar, "A Novel Unmanned Aerial Vehicle-Sink Enabled Mobility Model for Military Operations in Sparse Flying Ad-hoc Network", Transaction on Emerging Telecommunication Technologies, vol. 33, no. 5, art. no. e4466, 2022. DOI: https://doi.org/10.1002/ett.4466
View in Google Scholar
[35] M. Xu et al., "Improving Traditional Routing Protocols for Flying Ad Hoc Networks: A Survey", 2020 IEEE 6th International Conference on Computer and Communications (ICCC), Chengdu, China, 2020. DOI: https://doi.org/10.1109/ICCC51575.2020.9345206
View in Google Scholar
[36] S.N. Karam et al., "Inspection of Unmanned Aerial Vehicles in Oil and Gas Industry: Critical Analysis of Platforms, Sensors, Networking Architecture, and Path Planning", Journal of Electronic Imaging, vol. 32, no. 1, art. no. 011006, 2022. DOI: https://doi.org/10.1117/1.JEI.32.1.011006
View in Google Scholar
[37] M.H. Siddiqi et al., "FANET: Smart City Mobility off to a Flying Start with Self-organized Drone-based Networks", IET Communications, vol. 16, no. 10, pp. 1209-1217, 2022. DOI: https://doi.org/10.1049/cmu2.12291
View in Google Scholar
[38] A. Eroğlu and E. Onur, "Revisiting Slotted ALOHA: Density Adaptation in FANETs", Wireless Personal Communication, vol. 124, no. 2, pp. 1711-1740, 2022. DOI: https://doi.org/10.1007/s11277-021-09428-6
View in Google Scholar
[39] S.K. Maakar et al. "Performance Evaluation of AODV and DSR Routing Protocols for Flying Ad hoc Network Using Highway Mobility Model", Journal of Circuits, Systems and Computers, vol. 31, no. 1, art. no. 2250008, 2022. DOI: https://doi.org/10.1142/S0218126622500086
View in Google Scholar
[40] J. Souza et al., "A Proposal for Routing Protocol for FANET: A Fuzzy System Approach with QoE/QoS Guarantee", Wireless Communications and Mobile Computing, vol. 2019, art. no. 8709249, 2019. DOI: https://doi.org/10.1155/2019/8709249
View in Google Scholar
[41] A. Chriki, H. Touati, H. Snoussi, and F. Kamoun, "FANET: Communication, Mobility Models and Security Issues", Computer Networks, vol. 163, art. no. 106877, 2019. DOI: https://doi.org/10.1016/j.comnet.2019.106877
View in Google Scholar
[42] G. Secinti, P.B. Darian, B. Canberk, and K.R. Chowdhury, "SDNs in the Sky: Robust End-to-end Connectivity for Aerial Vehicular Networks", IEEE Communications Magazine, vol. 56, no. 1, pp. 16-21, 2018. DOI: https://doi.org/10.1109/MCOM.2017.1700456
View in Google Scholar
[43] H.R. Hussen, S.-C. Choi, J.-H. Park, and J. Kim, "Performance Analysis of MANET Routing Protocols for UAV Communications", 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 70-72, Prague, Czech Republic, 2018. DOI: https://doi.org/10.1109/ICUFN.2018.8436694
View in Google Scholar
[44] I. Mahmud and Y.-Z. Cho, "Adaptive Hello Interval in FANET Routing Protocols for Green UAVs", IEEE Access, vol. 7, pp. 63004-63015, 2019. DOI: https://doi.org/10.1109/ACCESS.2019.2917075
View in Google Scholar
[45] C. Li, L. Zheng, W. Xie, and P. Yang, "Ad Hoc Network Routing Protocol Based on Location and Neighbor Sensing", 2018 IEEE International Conference on Computer and Communication Engineering Technology (CCET), pp. 1-5, Beijing, China, 2018. DOI: https://doi.org/10.1109/CCET.2018.8542225
View in Google Scholar
[46] R. Fan et al., "Optimal Node Placement and Resource Allocation for UAV Relaying Network", IEEE Communications Letters, vol. 22, no. 4, pp. 808-811, 2018. DOI: https://doi.org/10.1109/LCOMM.2018.2800737
View in Google Scholar
[47] N. Palmieri and A. Serianni, "Overhead Analysis of a Bio-inspired Routing over FANET", 2022 30th Telecommunications Forum (TELFOR), Belgrade, Serbia, 2022. DOI: https://doi.org/10.1109/TELFOR56187.2022.9983785
View in Google Scholar
[48] A. Khan, F. Aftab, and Z. Zhang, "BICSF: Bio-inspired Clustering Scheme for FANETs", IEEE Access, vol. 7, pp. 31446-31456, 2019. DOI: https://doi.org/10.1109/ACCESS.2019.2902940
View in Google Scholar
[49] A. Yadav, A. Shastri, and S. Verma, "Experimental Analysis of ACO with Modified Firefly and Modified Genetic Algorithm for Routing in FANETs", in Optical and Wireless Technologies: Proceedings of OWT 2021, Springer, pp. 81-87, 2022. DOI: https://doi.org/10.1007/978-981-19-1645-8_9
View in Google Scholar
[50] Z. Zhang, K. Long, J. Wang, and F. Dressler, "On Swarm Intelligence Inspired Self-organized Networking: Its Bionic Mechanisms, Designing Principles and Optimization Approaches", IEEE Communications Surveys & Tutorials, vol. 16, no. 1, pp. 513-537, 2013. DOI: https://doi.org/10.1109/SURV.2013.062613.00014
View in Google Scholar
[51] A.K. Kar, "Bio Inspired Computing - A Review of Algorithms and Scope of Applications", Expert Systems with Applications, vol. 59, pp. 20-32, 2016. DOI: https://doi.org/10.1016/j.eswa.2016.04.018
View in Google Scholar
[52] K.N. Kaipa and D. Ghose, "Glowworm Swarm Optimization: Algorithm Development", in Glowworm Swarm Optimization, pp. 21-56, 2017. DOI: https://doi.org/10.1007/978-3-319-51595-3_2
View in Google Scholar
[53] A.H. Gandomi and A.H. Alavi, "Krill Herd: A New Bio-inspired Optimization Algorithm", Communications in Nonlinear Science and Numerical Simulation, vol. 17, pp. 4831-4845, 2012. DOI: https://doi.org/10.1016/j.cnsns.2012.05.010
View in Google Scholar
[54] G.-G. Wang, A.H. Gandomi, A.H. Alavi, and D. Gong, "A Comprehensive Review of Krill Herd Algorithm: Variants, Hybrids and Applications", Artificial Intelligence Review, vol. 51, pp. 119-148, 2019. DOI: https://doi.org/10.1007/s10462-017-9559-1
View in Google Scholar
[55] M. Dorigo, M. Birattari, and T. Stutzle, "Ant Colony Optimization", IEEE Computational Intelligence Magazine, vol. 1, pp. 28-39, 2006. DOI: https://doi.org/10.1109/MCI.2006.329691
View in Google Scholar
[56] N.A. Al-Aboody and H.S. Al-Raweshidy, "Grey Wolf Optimization-based Energy-efficient Routing Protocol for Heterogeneous Wireless Sensor Networks", 2016 4th International Symposium on Computational and Business Intelligence (ISCBI), Olten, Switzerland, 2016. -0.3pt DOI: https://doi.org/10.1109/ISCBI.2016.7743266
View in Google Scholar
[57] M.Y. Arafat and S. Moh, "Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications", IEEE Internet of Things Journal, vol. 6, pp. 8958-8976, 2019. DOI: https://doi.org/10.1109/JIOT.2019.2925567
View in Google Scholar
[58] G.A. Amran et al., "Efficient and Secure WiFi Signal Booster via Unmanned Aerial Vehicles WiFi Repeater Based on Intelligence Based Localization Swarm and Blockchain", Micromachines, vol. 13, art. no. 1924, 2022. DOI: https://doi.org/10.3390/mi13111924
View in Google Scholar
[59] C. Zhou, H.B. Gao, L. Gao, and W.G. Zhang, "Particle Swarm Optimization (PSO) Algorithm J", Application Research of Computers, vol. 12, pp. 7-11, 2003.
View in Google Scholar
[60] W. Bin and S. Zhongzhi, "A Clustering Algorithm Based on Swarm Intelligence", 2001 International Conferences on Info-Tech and Info-Net. Proceedings (Cat. No. 01EX479), Beijing, China, 2001.
View in Google Scholar
[61] O.T. Abdulhae, J.S. Mandeep, and M. Islam, "Cluster-based Routing Protocols for Flying Ad Hoc Networks (FANETs)", IEEE Access, vol. 10, pp. 32981-33004, 2022. DOI: https://doi.org/10.1109/ACCESS.2022.3161446
View in Google Scholar
[62] F. De Rango, M. Tropea, and P. Fazio, "Bio-inspired Routing over FANET in Emergency Situations to Support Multimedia Traffic", Proc. of the ACM MobiHoc Workshop on Innovative Aerial Communication Solutions for FIrst REsponders Network in Emergency Scenarios, pp. 12-17, 2019. DOI: https://doi.org/10.1145/3331053.3335033
View in Google Scholar
[63] B. Baran and R. Sosa, "A New Approach for AntNet Routing", Proc. of Ninth International Conference on Computer Communications and Networks (Cat. No. 00EX440), pp. 303-308, 2000. DOI: https://doi.org/10.1109/ICCCN.2000.885506
View in Google Scholar
[64] R. Sosa and B. Baran, "AntNet routing algorithm for data networks based on mobile agents", Revista Iberoamericana de Inteligencia Artificial, vol. 5, pp. 75-84, 2001 [Online] Available: (https://www.redalyc.org/pdf/925/92551210.pdf). DOI: https://doi.org/10.4114/ia.v5i12.711
View in Google Scholar
[65] P. Jacquet et al., "Optimized Link State Routing Protocol for Ad Hoc Networks", Proc. of IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century, pp. 62-68, 2001.
View in Google Scholar
[66] I.D. Chakeres and E.M. Belding-Royer, "AODV Routing Protocol Implementation Design", Proc. of 24th International Conference on Distributed Computing Systems Workshops, pp. 698-703, 2004. DOI: https://doi.org/10.1109/ICDCSW.2004.1284108
View in Google Scholar
[67] N.E.H. Bahloul, S. Boudjit, M. Abdennebi, and D.E. Boubiche, "Bio-inspired on Demand Routing Protocol for Unmanned Aerial Vehicles", 2017 26th International Conference on Computer Communication and Networks (ICCCN), Vancouver, Canada, 2017.
View in Google Scholar
[68] C.W. Reynolds, "Flocks, Herds and Schools: A Distributed Behavioral Model", Proc. of the 14th Annual Conference on Computer Graphics and Interactive Techniques, pp. 25-34, 1987. DOI: https://doi.org/10.1145/37401.37406
View in Google Scholar
[69] R.G. Braga, R.C. Da Silva, A.C. Ramos, and F. Mora-Camino, "Collision Avoidance Based on Reynolds Rules: A Case Study Using Quadrotors", Information Technology-New Generations, vol. 558, pp. 773-780, 2018. DOI: https://doi.org/10.1007/978-3-319-54978-1_96
View in Google Scholar
[70] Y. Yu et al., "Ant Colony Optimization Based Polymorphism-aware Routing Algorithm for Ad Hoc UAV Network", Multimedia Tools and Applications, vol. 75, pp. 14451-14476, 2016. DOI: https://doi.org/10.1007/s11042-015-3240-y
View in Google Scholar
[71] D.B. Johnson, D.A. Maltz, and J. Broch, "DSR: The Dynamic Source Routing Protocol for Multi-hop Wireless Ad Hoc Networks", Monarch Project at Carnegie Mellon University, 2001 [Online] Available: (https://www.cse.iitb.ac.in/ mythili/teaching/cs653_spring2014/references/dsr.pdf).
View in Google Scholar
[72] J. Wang, E. Osagie, P. Thulasiraman, and R.K. Thulasiram, "HOPNET: A Hybrid Ant Colony Optimization Routing Algorithm for Mobile Ad Hoc Network", Ad Hoc Networks, vol. 7, pp. 690-705, 2009. -0.2pt DOI: https://doi.org/10.1016/j.adhoc.2008.06.001
View in Google Scholar
[73] M. Aissani, M. Fenouche, H. Sadour, and A. Mellouk, "Ant-DSR: Cache Maintenance Based Routing Protocol for Mobile Ad Hoc Networks", The Third Advanced International Conference on Telecommunications (AICT’07), Morne, Mauritius, 2017.
View in Google Scholar
[74] A.M. Ellison, "Bayesian Inference in Ecology", Ecology Letters, vol. 7, pp. 509-520, 2004. DOI: https://doi.org/10.1111/j.1461-0248.2004.00603.x
View in Google Scholar
[75] H.F. Wedde et al., "BeeAdHoc: An Energy Efficient Routing Algorithm for Mobile Ad Hoc Networks Inspired by Bee Behavior", Proc. of the 7th Annual Conference on Genetic and Evolutionary Computation, pp. 153-160, 2005. DOI: https://doi.org/10.1145/1068009.1068034
View in Google Scholar
[76] J.R. Riley et al., "The Flight Paths of Honeybees Recruited by the Waggle Dance", Nature, vol. 435, pp. 205-207, 2005. DOI: https://doi.org/10.1038/nature03526
View in Google Scholar
[77] S. Dong, T. Lin, J.C. Nieh, and K. Tan, "Social Signal Learning of the Waggle Dance in Honey Bees", Science, vol. 379, pp. 1015-1018, 2023. DOI: https://doi.org/10.1126/science.ade1702
View in Google Scholar
[78] F. Aftab, A. Khan, and Z. Zhang, "Hybrid Self-organized Clustering Scheme for Drone Based Cognitive Internet of Things", IEEE Access, vol. 7, pp. 56217-56227, 2019. DOI: https://doi.org/10.1109/ACCESS.2019.2913912
View in Google Scholar
[79] Y. Meraihi, A. Ramdane-Cherif, D. Acheli, and M. Mahseur, "Dragonfly Algorithm: A Comprehensive Review and Applications", Neural Computing and Applications, vol. 32, pp. 16625-16646, 2020. DOI: https://doi.org/10.1007/s00521-020-04866-y
View in Google Scholar
[80] S. Mirjalili, "Dragonfly Algorithm: A New Meta-heuristic Optimization Technique for Solving Single-objective, Discrete, and Multi-objective Problems", Neural Computing and Applications, vol. 27, pp. 1053-1073, 2016. DOI: https://doi.org/10.1007/s00521-015-1920-1
View in Google Scholar
[81] G. Jones and B.M. Siemers, "The Communicative Potential of Bat Echolocation Pulses", Journal of Comparative Physiology A, vol. 197, pp. 447-457, 2011. DOI: https://doi.org/10.1007/s00359-010-0565-x
View in Google Scholar
[82] S. Hameed et al., "An Improved iBAT-COOP Protocol for Cooperative Diversity in FANETs", Computers, Materials & Continua, vol. 67, pp. 2527-2546, 2021. DOI: https://doi.org/10.32604/cmc.2021.013896
View in Google Scholar
[83] S. Hameed et al., "Link and Loss Aware GW-COOP Routing Protocol for FANETs", IEEE Access, vol. 9, pp. 110544-110557, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3101361
View in Google Scholar
[84] R.O. Peterson et al., "Leadership Behavior in Relation to Dominance and Reproductive Status in Gray Wolves, Canis Lupus", Canadian Journal of Zoology, vol. 80, pp. 1405-1412, 2002. DOI: https://doi.org/10.1139/z02-124
View in Google Scholar
[85] S. Yang et al., "Bio-inspired Multi-hop Clustering Algorithm for FANET", Ad Hoc Networks, vol. 154, art. no. 103355, 2024. DOI: https://doi.org/10.1016/j.adhoc.2023.103355
View in Google Scholar
[86] X. Zhang et al., "An Improved Physarum Polycephalum Algorithm for the Shortest Path Problem", The Scientific World Journal, pp. 1-9, 2014. DOI: https://doi.org/10.1155/2014/487069
View in Google Scholar
[87] A.M. Reynolds and C.J. Rhodes, "The Lévy Flight Paradigm: Random Search Patterns and Mechanisms", Ecology, vol. 90, pp. 877-887, 2009. DOI: https://doi.org/10.1890/08-0153.1
View in Google Scholar
[88] A. Kout et al., "A Hybrid Optimization Solution for UAV Network Routing", Engineering, Technology & Applied Science Research, vol. 13, pp. 10270-10278, 2023. DOI: https://doi.org/10.48084/etasr.5661
View in Google Scholar
[89] F. A. Hashim et al., "Honey Badger Algorithm: New Metaheuristic Algorithm for Solving Optimization Problems", Mathematics and Computers in Simulation, vol. 192, pp. 84-110, 2022. DOI: https://doi.org/10.1016/j.matcom.2021.08.013
View in Google Scholar
[90] A. Beghriche, "An Adaptive Secure and Efficient Bio-inspired Routing Protocol for Effective Cooperation in FANETs", Ingénierie des Systèmes d’Information, vol. 28, pp. 49-66, 2023. DOI: https://doi.org/10.18280/isi.280106
View in Google Scholar
[91] F.S. Abu-Mouti and M.E. El-Hawary, "Overview of Artificial Bee Colony (ABC) Algorithm and its Applications", 2012 IEEE International Systems Conference SysCon 2012, Vancouver, Canada, 2012. DOI: https://doi.org/10.1109/SysCon.2012.6189539
View in Google Scholar
[92] K.M. Passino, "Bacterial Foraging Optimization", in: Innovations and Developments of Swarm Intelligence Applications, pp. 219-234, 2010. DOI: https://doi.org/10.4018/978-1-4666-1592-2.ch013
View in Google Scholar
[93] S. Mirjalili, "Moth-flame Optimization Algorithm: A Novel Nature-inspired Heuristic Paradigm", Knowledge-Based Systems, vol. 89, pp. 228-249, 2015. DOI: https://doi.org/10.1016/j.knosys.2015.07.006
View in Google Scholar
[94] A.F. Fard and M. Hajiaghaei-Keshteli, "Red Deer Algorithm (RDA); A New Optimization Algorithm Inspired by Red Deer’s Mating", International Conference on Industrial Engineering, Tehran, Iran, 2016.
View in Google Scholar
[95] A. Meier and J.S. Thompson, "Cooperative Diversity in Wireless Networks", 6th IEE International Conference on 3G and Beyond, Stevenage, UK, 2005. DOI: https://doi.org/10.1049/cp:20050189
View in Google Scholar
[96] V.A. Maistrenko, L.V. Alexey, and V.A. Danil, "Experimental Estimate of Using the Ant Colony Optimization Algorithm to Solve the Routing Problem in FANET", 2016 International Siberian Conference on Control and Communications (SIBCON), Moscow, Russia, 2016. DOI: https://doi.org/10.1109/SIBCON.2016.7491805
View in Google Scholar
[97] A. Heidari, N.J. Navimipour, M. Unal, and G. Zhang, "Machine Learning Applications in Internet-of-drones: Systematic Review, Recent Deployments, and Open Issues", ACM Computing Surveys, vol. 55, pp. 1-45, 2023. DOI: https://doi.org/10.1145/3571728
View in Google Scholar
[98] O. Ceviz, S. Sen, and P. Sadioglu, "A Survey of Security in UAVs and FANETs: Issues, Threats, Analysis of Attacks, and Solutions", IEEE Communications Surveys & Tutorials, 2024. DOI: https://doi.org/10.1109/COMST.2024.3515051
View in Google Scholar
[99] H. Yang and Z. Liu, "An optimization routing protocol for FANETs", EURASIP J. on Wireless Communications and Networking, art. no. 120, 2019. DOI: https://doi.org/10.1186/s13638-019-1442-0
View in Google Scholar
[100] S. Bharany et al., "Wildfire Monitoring Based on Energy Efficient Clustering Approach for FANETS", Drones, vol. 6, art. no. 193, 2022. DOI: https://doi.org/10.3390/drones6080193
View in Google Scholar
[101] D. Bein, W. Bein, A. Karki, and B.B. Madan, "Optimizing Border Patrol Operations Using Unmanned Aerial Vehicles", 2015 12th International Conference on Information Technology-New Generations, Las Vegas, USA, 2015. DOI: https://doi.org/10.1109/ITNG.2015.83
View in Google Scholar
[102] K. Mariyappan, M.S. Christo, and R. Khilar, "Implementation of FANET Energy Efficient AODV Routing Protocols for Flying Ad Hoc Networks FEEAODV", Materialstoday Proceeding, 2021. DOI: https://doi.org/10.1016/j.matpr.2021.02.673
View in Google Scholar
[103] N. Mansoor et al., "Cognitive Radio Ad Hoc Network Architectures: A Survey", Wireless Personal Communications, vol. 81, pp. 1117-1142, 2015. DOI: https://doi.org/10.1007/s11277-014-2175-3
View in Google Scholar
[104] A. Hussain et al., "Taking FANET to Next Level: The Contrast Evaluation of Moth-and-ant with Bee Ad Hoc Routing Protocols for Flying Ad Hoc Networks", ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, vol. 10, pp. 321-337, 2021. DOI: https://doi.org/10.14201/ADCAIJ2021104321337
View in Google Scholar
[105] H.S. Mansour et al., "Cross-layer and Energy-aware AODV Routing Protocol for Flying Ad Hoc Networks", Sustainability, vol. 14, art. no. 8980, 2022. DOI: https://doi.org/10.3390/su14158980
View in Google Scholar
[106] R. Khaleghnasab et al., "An Energy and Load Aware Multipath Routing Protocol in the Internet of Things", Management Strategies and Engineering Sciences, vol. 7, pp. 1-15, 2020. DOI: https://doi.org/10.61838/msesj.7.3.1
View in Google Scholar
[107] P. Kaur, A. Singh, and S.S. Gill, "RGIM: an Integrated Approach to Improve QoS in AODV, DSR and DSDV Routing Protocols for FANETS Using the Chain Mobility Model", The Computer Journal, vol. 63, pp. 1500-1512, 2020. DOI: https://doi.org/10.1093/comjnl/bxaa040
View in Google Scholar
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