Open Access Open Access  Restricted Access Subscription Access

A Novel Golden Eagle Optimizer Based Trusted Ad Hoc On-Demand Distance Vector (GEO-TAODV) Routing Protocol


Affiliations
1 Department of Information Science and Engineering , SDM College of Engineering and Technology, Dharwad, Karnataka, India
2 Department of Information Science and Engineering, SDM College of Engineering & Technology, Dharwad, Karnataka, India
 

Mobile Ad-hoc Networks (MANETs) are a type of wireless network that allows people gaining more ubiquitous, as seen by their exponential rise over the last decade. They are made up of mobile nodes that connect remotely. The network's efficiency is highly dependent on the routing protocol used. This provided an opportunity for academics to design routing methods capable of increasing network efficiency. The literature focuses on building algorithms for route selection based on either the energy level or the distance between source and destination. However, there are other elements that affect the network's data transmission efficiency. Thus, this study work offers a unique Golden Eagle Optimizer-based Trusted Ad-hoc On-Demand Distance Vector (GEO-TAODV) routing protocol that optimizes route selection on the basis of criteria such as priority queue, trust degree, delay, hop count, and energy level. The trustworthiness of potential routes is determined using a consensus network model. By satisfying the reward expectations of the given multi-objective function, the suggested GEO method assists in determining the most efficient and trusted route for data transfer. Thus, the GEO-TAODV routing protocol assures that data is transmitted efficiently via a trusted path. The proposed GEO-TAODV protocol is simulated and compared to existing AODV and AODV-version 2 routing methods.

Keywords

AODV, Consensus, Golden Eagle Optimizer, GEO-TAODV, MANET.
User
Notifications
Font Size

  • Mafirabadza, C., Makausi, T. T., & Khatri, P. (2016, August). Efficient power aware AODV routing protocol in MANET. In Proceedings of the International Conference on Advances in Information Communication Technology & Computing (pp. 1-6).
  • Bai, R., &Singhal, M. (2006). DOA: DSR over AODV routing for mobile ad hoc networks. IEEE transactions on Mobile Computing, 5(10), 1403-1416.
  • Mhala, N. N., &Choudhari, N. K. (2010). Implementation possibilities for AODV routing protocol in real world. International Journal of Distributed and Parallel Systems (IJDPS), 1(2), 118-127.
  • Liu, L., Zhu, L., Lin, L., & Wu, Q. (2012). Improvement of AODV routing protocol with QoS support in wireless mesh networks. Physics Procedia, 25, 1133-1140.
  • Abu-Ein, A., & Nader, J. (2014). An enhanced AODV routing protocol for MANETs. International Journal of Computer Science Issues (IJCSI), 11(1), 54.
  • Abbas, N. I., Ilkan, M., &Ozen, E. (2015). Fuzzy approach to improving route stability of the AODV routing protocol. EURASIP Journal on Wireless Communications and Networking, 2015(1), 1-11.
  • Maurya, P. K., Sharma, G., Sahu, V., Roberts, A., Srivastava, M., & Scholar, M. T. (2012). An overview of AODV routing protocol. International Journal of Modern Engineering Research (IJMER), 2(3), 728-732.
  • Liu, S., Yang, Y., & Wang, W. (2013). Research of AODV routing protocol for ad hoc networks1. AASRI Procedia, 5, 21-31.
  • Ding, B., Chen, Z., Wang, Y., & Yu, H. (2011, November). An improved AODV routing protocol for VANETs. In 2011 international conference on wireless communications and signal processing (wcsp) (pp. 1-5). IEEE.
  • Navale, M. M. P., &Chavan, G. T. (2014). Survey on QoS Improving Methods in MANET. International Journal of Engineering and Technology, 3(12), 22-25.
  • Kumar, S. R., Gayathri, N., &Balusamy, B. (2019). Enhancing network lifetime through power-aware routing in MANET. International Journal of Internet Technology and Secured Transactions, 9(1-2), 96-111.
  • Chitkara, M., & Ahmad, M. W. (2014). Review on manet: characteristics, challenges, imperatives and routing protocols. International journal of computer science and mobile computing, 3(2), 432-437.
  • Eichler, S., & Roman, C. (2006, October). Challenges of secure routing in MANETs: A simulative approach using AODV-SEC. In 2006 IEEE International Conference on Mobile Ad Hoc and Sensor Systems (pp. 481-484). IEEE.
  • Fang, W., Zhang, W., Xiao, J., Yang, Y., & Chen, W. (2017). A source anonymity-based lightweight secure AODV protocol for fog-based MANET. Sensors, 17(6), 1421.
  • Shashwat, Y., Pandey, P., Arya, K. V., & Kumar, S. (2017). A modified AODV protocol for preventing blackhole attack in MANETs. Information Security Journal: A Global Perspective, 26(5), 240-248.
  • Shaf, A., Ali, T., Draz, U., &Yasin, S. (2018). Energy based performance analysis of AODV routing protocol under TCP and UDP environments. EAI Endorsed Transactions on Energy Web, 5(17).
  • Jubair, M. A., Khaleefah, S. H., Budiyono, A., Mostafa, S. A., & Mustapha, A. (2018). Performance evaluation of AODV and OLSR routing protocols in MANET environment. Int. J. Adv. Sci. Eng. Inf. Technol, 8(4), 1277-1283.
  • Kaur, T., & Kumar, R. (2018, August). Mitigation of blackhole attacks and wormhole attacks in wireless sensor networks using aodv protocol. In 2018 IEEE International Conference on Smart Energy Grid Engineering (SEGE) (pp. 288-292). IEEE.
  • Darabkh, K. A., Judeh, M. S., Salameh, H. B., &Althunibat, S. (2018). Mobility aware and dual phase AODV protocol with adaptive hello messages over vehicular ad hoc networks. AEU-International Journal of Electronics and Communications, 94, 277-292.
  • Gurung, S., & Chauhan, S. (2019). A dynamic threshold based algorithm for improving security and performance of AODV under black-hole attack in MANET. Wireless Networks, 25(4), 1685-1695.
  • Gupta, P., Goel, P., Varshney, P., &Tyagi, N. (2019). Reliability factor based AODV protocol: Prevention of black hole attack in MANET. In Smart Innovations in Communication and Computational Sciences (pp. 271-279). Springer, Singapore.
  • Sankara Narayanan, S., &Murugaboopathi, G. (2020). Modified secure AODV protocol to prevent wormhole attack in MANET. Concurrency and Computation: Practice and Experience, 32(4), e5017.
  • Bamhdi, A. M. (2020). Efficient dynamic-power AODV routing protocol based on node density. Computer Standards & Interfaces, 70, 103406.
  • Singh, H., & Singh, P. (2017). Enhanced new clustering ant colony optimization based routing protocol AODV-R. International Journal of Computer Applications, 160(9).
  • Zhang, M., Yang, M., Wu, Q., Zheng, R., & Zhu, J. (2018). Smart perception and autonomic optimization: A novel bio-inspired hybrid routing protocol for MANETs. Future generation computer systems, 81, 505-513.
  • Sarkar, D., Choudhury, S., &Majumder, A. (2018). Enhanced-Ant-AODV for optimal route selection in mobile ad-hoc network. Journal of King Saud University-Computer and Information Sciences.
  • Hassan, M. H., Mostafa, S. A., Mohammed, M. A., Ibrahim, D. A., Khalaf, B. A., & Al-Khaleefa, A. S. (2019). Integrating African Buffalo optimization algorithm in AODV routing protocol for improving the QoS of MANET. Journal of Southwest Jiaotong University, 54(3).
  • Janakiraman, S. (2018). A hybrid ant colony and artificial bee colony optimization algorithm-based cluster head selection for IoT. Procedia computer science, 143, 360-366.
  • Sun, Z., Wei, M., Zhang, Z., & Qu, G. (2019). Secure routing protocol based on multi-objective ant-colony-optimization for wireless sensor networks. Applied Soft Computing, 77, 366-375.
  • Abdali, T. A. N., Hassan, R., Muniyandi, R. C., MohdAman, A. H., Nguyen, Q. N., & Al-Khaleefa, A. S. (2020). Optimized particle swarm optimization algorithm for the realization of an enhanced energy-aware location-aided routing protocol in MANET. Information, 11(11), 529.
  • Bhardwaj, A., & El-Ocla, H. (2020). Multipath routing protocol using genetic algorithm in mobile ad hoc networks. IEEE Access, 8, 177534-177548.
  • Divya, K., & Srinivasan, B. Energy-Aware-AODV: Optimized Route Selection Process based on Ant Colony Optimization–Bacterial Foraging Algorithm (ACO-BFA). European Journal of Molecular & Clinical Medicine, 8(03), 2021.
  • Goyal, A., Sharma, V. K., Kumar, S., &Poonia, R. C. (2021). Hybrid AODV: An Efficient Routing Protocol for Manet Using MFR and Firefly Optimization Technique. Journal of Interconnection Networks, 21(01), 2150004.
  • Mohammadi-Balani, A., Nayeri, M. D., Azar, A., &Taghizadeh-Yazdi, M. (2021). Golden eagle optimizer: A nature-inspired metaheuristic algorithm. Computers & Industrial Engineering, 152, 107050.
  • Chakeres, I. D., & Belding-Royer, E. M. (2004, March). AODV routing protocol implementation design. In 24th International Conference on Distributed Computing Systems Workshops, 2004. Proceedings. (pp. 698-703). IEEE.
  • Clausen, T., Yi, J., & De Verdiere, A. C. (2012, September). Loadng: Towards aodv version 2. In 2012 IEEE Vehicular Technology Conference (VTC Fall) (pp. 1-5). IEEE.

Abstract Views: 37

PDF Views: 1




  • A Novel Golden Eagle Optimizer Based Trusted Ad Hoc On-Demand Distance Vector (GEO-TAODV) Routing Protocol

Abstract Views: 37  |  PDF Views: 1

Authors

Sachidanand S. Joshi
Department of Information Science and Engineering , SDM College of Engineering and Technology, Dharwad, Karnataka, India
Sangappa Ramachandra Biradar
Department of Information Science and Engineering, SDM College of Engineering & Technology, Dharwad, Karnataka, India

Abstract


Mobile Ad-hoc Networks (MANETs) are a type of wireless network that allows people gaining more ubiquitous, as seen by their exponential rise over the last decade. They are made up of mobile nodes that connect remotely. The network's efficiency is highly dependent on the routing protocol used. This provided an opportunity for academics to design routing methods capable of increasing network efficiency. The literature focuses on building algorithms for route selection based on either the energy level or the distance between source and destination. However, there are other elements that affect the network's data transmission efficiency. Thus, this study work offers a unique Golden Eagle Optimizer-based Trusted Ad-hoc On-Demand Distance Vector (GEO-TAODV) routing protocol that optimizes route selection on the basis of criteria such as priority queue, trust degree, delay, hop count, and energy level. The trustworthiness of potential routes is determined using a consensus network model. By satisfying the reward expectations of the given multi-objective function, the suggested GEO method assists in determining the most efficient and trusted route for data transfer. Thus, the GEO-TAODV routing protocol assures that data is transmitted efficiently via a trusted path. The proposed GEO-TAODV protocol is simulated and compared to existing AODV and AODV-version 2 routing methods.

Keywords


AODV, Consensus, Golden Eagle Optimizer, GEO-TAODV, MANET.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F209986