Hybrid Invasive Weed and Grasshopper Optimization based on AI Approach for Enhanced Routing in FANETs.
Keywords:
Flying ad hoc networks, Clustering, Routing, Invasive weed optimization algorithm, Grasshopper optimization algorithmAbstract
Methods of clustering show promise as instruments for ensuring the scalability and maintainability of massive FANETs. However, it is challenging to uphold the FANETs because of Unmanned Aerial Vehicles (UAVs). FANETS routing is more difficult than MANETs or VANETs because of these topological constraints. When static and dynamic routings aren't enough to fix a complex routing problem, clustering methodologies based on AI can be employed to find a solution. This paper proposes a method for solving such routing issues by incorporating the benefits of the Invasive Weed Optimization Algorithm (IWOA) into the Grasshopper Optimization Algorithm (GOA). This method is referred to as Hybrid Invasive Weed Improved Grasshopper Optimization Algorithm-based efficient Routing (HIWIGOA-R). In particular, the random walk tactic is used to avoid the potential for a single solution to dominate. The traditional GOA's exploitation coefficient was adjusted through the use of grouping to achieve a more equitable rate. The effectiveness of the suggested approach is measured in a variety of ways. These include packet delivery ratio, end-to-end delay, energy consumption and network lifetime. The experimental consequences presented here show that the suggested algorithm outperforms the current top methods in the field.
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Wheeb, A. H., Nordin, R., Samah, A. A., Alsharif, M. H., & Khan, M. A. (2021). Topology-based routing protocols and mobility models for flying ad hoc networks: A contemporary review and future research directions. Drones, 6(1), 9.
Pasandideh, F., da Costa, J. P. J., Kunst, R., Islam, N., Hardjawana, W., & Pignaton de Freitas, E. (2022). A review of flying ad hoc networks: Key characteristics, applications, and wireless technologies. Remote Sensing, 14(18), 4459.
Bharany, S., Sharma, S., Badotra, S., Khalaf, O. I., Alotaibi, Y., Alghamdi, S., & Alassery, F. (2021). Energy-efficient clustering scheme for flying ad-hoc networks using an optimized LEACH protocol. Energies, 14(19), 6016.
Oubbati, O. S., Atiquzzaman, M., Lorenz, P., Tareque, M. H., & Hossain, M. S. (2019). Routing in flying ad hoc networks: Survey, constraints, and future challenge perspectives. IEEE Access, 7, 81057-81105.
Khan, I. U., Qureshi, I. M., Aziz, M. A., Cheema, T. A., & Shah, S. B. H. (2020). Smart IoT control-based nature inspired energy efficient routing protocol for flying ad hoc networks (FANET). IEEE Access, 8, 56371-56378.
Arafat, M. Y., & Moh, S. (2021). A Q-learning-based topology-aware routing protocol for flying ad hoc networks. IEEE Internet of Things Journal, 9(3), 1985-2000.
Liu, J., Wang, Q., He, C., Jaffrès-Runser, K., Xu, Y., Li, Z., & Xu, Y. (2020). QMR: Q-learning based multi-objective optimization routing protocol for flying ad hoc networks. Computer Communications, 150, 304-316.
Kaur, M., & Verma, S. (2020). Flying ad-hoc network (FANET): challenges and routing protocols. Journal of Computational and Theoretical Nanoscience, 17(6), 2575-2581.
Azevedo, M. I. B., Coutinho, C., Toda, E. M., Carvalho, T. C., & Jailton, J. (2020). Wireless communications challenges to flying ad hoc networks (FANET). Mobile Computing, 3.
Agrawal, J., & Kapoor, M. (2021). A comparative study on geographic‐based routing algorithms for flying ad‐hoc networks. Concurrency and Computation: Practice and Experience, 33(16), e6253.
Tsao, K. Y., Girdler, T., & Vassilakis, V. G. (2022). A survey of cyber security threats and solutions for UAV communications and flying ad-hoc networks. Ad Hoc Networks, 133, 102894.
Arafat, M. Y., Poudel, S., & Moh, S. (2020). Medium access control protocols for flying ad hoc networks: A review. IEEE Sensors Journal, 21(4), 4097-4121.
Lee, S. W., Ali, S., Yousefpoor, M. S., Yousefpoor, E., Lalbakhsh, P., Javaheri, D., ... & Hosseinzadeh, M. (2021). An energy-aware and predictive fuzzy logic-based routing scheme in Flying Ad Hoc Networks (FANETs). IEEE Access, 9, 129977-130005.
Xue, Q., Yang, Y., Yang, J., Tan, X., Sun, J., Li, G., & Chen, Y. (2023). QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks. Drones, 7(7), 459.
Anwekar, D., & Phulre, S. (2023, July). Analysis of Congestion Control Techniques to Improve QoS and Frequent Communication in FANET. In 2023 World Conference on Communication & Computing (WCONF) (pp. 1-7). IEEE.
. Rahman, K., Aziz, M. A., Usman, N., Kiren, T., Cheema, T. A., Shoukat, H., ... & Sajid, A. (2023). Cognitive Lightweight Logistic Regression-Based IDS for IoT-Enabled FANET to Detect Cyberattacks. Mobile Information Systems, 2023.
Hosseinzadeh, M., Mohammed, A. H., Alenizi, F. A., Malik, M. H., Yousefpoor, E., Yousefpoor, M. S., ... & Tightiz, L. (2023). A novel fuzzy trust-based secure routing scheme in flying ad hoc networks. Vehicular Communications, 44, 100665.
Kumar, S., Rathore, N. K., Prajapati, M., & Sharma, S. K. (2023). SF-GoeR: an emergency information dissemination routing in flying Ad-hoc network to support healthcare monitoring. Journal of Ambient Intelligence and Humanized Computing, 14(7), 9343-9353.
Kumar, S., Raw, R. S., & Bansal, A. (2023). LoCaL: Link‐optimized cone‐assisted location routing in flying ad hoc networks. International Journal of Communication Systems, 36(2), e5375.
Lansky, J., Rahmani, A. M., Malik, M. H., Yousefpoor, E., Yousefpoor, M. S., Khan, M. U., & Hosseinzadeh, M. (2023). An energy-aware routing method using firefly algorithm for flying ad hoc networks. Scientific Reports, 13(1), 1323.
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