Optimization of MANETs Communication Using AOMDV With Novel Aging Multi Population Strategy for Effectual Energy Utilization
Abstract
In today’s world wireless technologies plays vital role for many real world applications particularly the Mobile Ad-hoc Network (MANET) with bidirectional transmission capacity through numerous intermediary nodes is having dynamic scope in near future. Whereas, packet collision is regarded as the most important restrictions in MANETs since nodes move randomly through the network at unpredictable speeds, increasing the likelihood of collision and degrading throughput, routing overhead, and end-to-end delay. Additionally, a topological shift and link instability caused by frequent node mobility lower the rate of data delivery. The probability of traffic crowding increases at the intermediary nodes due to limited possible routes to the destination network, which affects the successful delivery of packets, especially with real-world applications on MANETs. In the proposed work, a novel strategy of age to evaluate each particle's local area search capacity is anticipated with Aging Multi Population Optimization (AMPO). The particles are divided into distinct age groups according to their ages so that population variety can be maintained when searching. Particles within every group of age can only choose those in younger or from their own clusters / groups as preferred neighbors. To choose the optimum route to the destination, we optimise the many pathways that the Adhoc On-demand Multipath Distance Vector (AOMDV) mechanism returned. The most ideal route is thought to be the one with the highest value for fitness. In order to speed up convergence, we also create a parameter setting mechanism based on age groups, where particles in various age groups have distinct parameters. Finally, we evaluate our suggested approach in comparison to AOMDV-TA and EHO-AOMDV. For the performance assessment of the suggested model, network overhead, throughput, delay, energy usage, and delivery of packets range as vital aspects.
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Sandeep Monga, J.L. Rana, Jitendra Agarwal, Clustering schemes in mobile ad-hoc network (MANET): a review, 08, Int. J. Sci. Technol. Res. 8 (AUGUST 2019), 2277–8616.
L.M. Tuan, L.H. Son, H.V. Long, L.R. Priya, K.R. Soundar, Y.H. Robinson, R. Kumar, ITFDS: channel-aware integrated time and frequency-based downlink LTE scheduling in MANET, Sensors 20 (12) (2020) 1–20.
Vargheese, M., Vanithamani, S., David, D. S., & Rao, G. R. K. (2023). Design of Fuzzy Logic Control Framework for QoS Routing in MANET. Intelligent Automation & Soft Computing, 35(3).
P. Elamparithi, K. RubaSoundar, Trusted sensing model for mobile ad hoc network using differential evolution algorithm, Int. J. Information. Technol. Control 49 (4) (December 2020) 556 563.
Houlding, P. (2023). A Review of the Replicability and Implementation of the Efficient Clustering Scheme for MANETs in Remote Canadian Communities.
V. Selvakumar, K. RubaSoundar, Deep Reinforcement Learning for Building Honeypots against Runtime DoS Attack” International Journal of Intelligent Systems, Wiley online library, October 2021, https://doi.org/10.1002/int.22708.
A.V. Vasilakos, Z. Li, G. Simon, W. You, Information-centric network: research challenges and opportunities, J. Netw. Comput. Appl. 52 (2015) 1–10 (Elsevier Ltd).
Preethi, P., & Asokan, R. (2020, December). Neural network oriented roni prediction for embedding process with hex code encryption in dicom images. In Proceedings of the 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India (pp. 18-19).
Bai, D. P., & Preethi, P. (2016). Security Enhancement of Health Information Exchange Based on Cloud Computing System. International Journal of Scientific Engineering and Research, 4(10), 79-82.
Karthick, K., & Asokan, R. (2021). Mobility aware quality enhanced cluster based routing protocol for mobile ad-hoc networks using hybrid optimization algorithm. Wireless Personal Communications, 119(4), 3063-3087.
Nivetha, S. K., Asokan, R., & Senthilkumaran, N. (2019, May). Metaheuristics in Mobile AdHoc Network Route Optimization. In 2019 TEQIP III Sponsored International Conference on Microwave Integrated Circuits, Photonics and Wireless Networks (IMICPW) (pp. 414-418). IEEE.
Sunil Pathak, Sonal Jain, An optimized stable clustering algorithm for mobile ad hoc networks, Pathak Jain EURASIP J. Wireless Commun. Networking (2017) (2017) 51, https://doi.org/10.1186/s13638-017-0832.
Z. Chen, W. Zhou, S. Wu, and L. Cheng, ``An adaptive on-demand mul-tipath routing protocol with QoS support for high-speed MANET,'' IEEEAccess, vol. 8, pp. 44760_44773, 2020.
A. Taha, R. Alsaqour, M. Uddin, M. Abdelhaq, and T. Saba, ``Energyef_cient multipath routing protocol for mobile Ad-hoc network using the_tness function,'' IEEE Access, vol. 5, pp. 10369_10381, 2017.
S. Sarhan and S. Sarhan, ``Elephant herding optimization Adhoc on-demand multipath distance vector routing protocol forMANET,'' IEEE Access, vol. 9, pp. 39489_39499, 2021, doi: 10.1109/ACCESS.2021.3065288.
Al-Shareeda, M. A., & Manickam, S. (2022). Man-in-the-middle attacks in mobile ad hoc networks (MANETs): Analysis and evaluation. Symmetry, 14(8), 1543.
Singh, S., Pise, A., Alfarraj, O., Tolba, A., & Yoon, B. (2022). A cryptographic approach to prevent network incursion for enhancement of QoS in sustainable smart city using MANET. Sustainable Cities and Society, 79, 103483.
A. Bhardwaj and H. El-Ocla, ``Multipath routing protocol usinggenetic algorithm in mobile Ad hoc networks,'' IEEE Access, vol. 8, pp. 177534_177548, 2020, doi:m10.1109/ACCESS.2020.3027043.
Z. Lin and J. Sun, ``Routing protocol based on link stability in MANET,''in Proc. World Automat. Congr. (WAC), Aug. 2021, pp. 260_264, doi:10.23919/WAC50355.2021.9559469.
Skokowski, P., Malon, K., & Łopatka, J. (2022). Building the Electromagnetic Situation Awareness in MANET Cognitive Radio Networks for Urban Areas. Sensors, 22(3), 716.
V. Tilwari, A. Bani-Bakr, F. Qamar, M. N. Hindia, D. N. K. Jayakody,and R. Hassan, ``Mobility and queue length aware routing approachfor network stability and load balancing in MANET,'' in Proc.Int. Conf. Electr. Eng. Informat. (ICEEI), Oct. 2021, pp. 1_5, doi:10.1109/ICEEI52609.2021.9611119.
M. Farsi, M. Badawy, M. Moustafa, H. Arafat Ali, and Y. Abdulazeem,``A congestion-aware clustering and routing (CCR) protocol for mitigatingcongestion in WSN,'' IEEE Access, vol. 7, pp. 105402_105419, 2019.
P. Pal, S. Tripathi, and C. Kumar, ``Bandwidth estimation in high mobilityscenarios of IEEE 802.11 infrastructure-less mobile Ad hoc networks,'' Int.J. Commun. Syst., vol. 32, no. 15, p. e4080, Oct. 2019.
Patel, S., & Pathak, H. (2022). A mathematical framework for link failure time estimation in MANETs. Engineering Science and Technology, an International Journal, 25, 100984.
N. R. Patel, S. Kumar, and S. K. Singh, ``Energy and collision awareWSN routing protocol for sustainable and intelligent IoT applications,''IEEE Sensors J., vol. 21, no. 22, pp. 25282_25292, Nov. 2021, doi:10.1109/JSEN.2021.3076192.
U. Srilakshmi, N. Veeraiah, Y. Alotaibi, S. A. Alghamdi, O. I. Khalaf,and B. V. Subbayamma, ``An improved hybrid secure multipath routingprotocol for MANET,'' IEEE Access, vol. 9, pp. 163043_163053, 2021,doi: 10.1109/ACCESS.2021.3133882.
N. Muruganantham and H. El-Ocla, ``Routing using genetic algorithmin a wireless sensor network,'' Wireless Pers. Commun., vol. 111, no. 4,pp. 2703_2732, Apr. 2020.
F. Sarkohaki, R. Fotohi, and V. Ashra_an, ``An ef_cient routing protocolin mobile Ad-hoc networks by using arti_cial immune system,'' 2020.
M. Ghafouri Vaighan and M. A. JabraeilJamali, ``A multipath QoS multi-cast routing protocol based on link stability and route reliability in mobileAd-hoc networks,'' J. Ambient Intell. Humanized Comput., vol. 10, no. 1,pp. 107_123, Jan. 2019, doi: 10.1007/s12652-017-0609-y.
A. Naushad, G. Abbas, Z. H. Abbas, and A. Pagourtzis, ``Novel strategies for path stability estimation under topology change using hello messaging in MANETs,'' Ad Hoc Netw., vol. 87, pp. 76_99, May 2019.
R. Hemalatha, R. Umamaheswari, and S. Jothi, ``An effcient stable node selection based on Garson's pruned recurrent neural network and MSO model for multipath routing in MANET,'' Concurrency Comput., Pract.Exper., vol. 34, no. 21, Sep. 2022, doi: 10.1002/cpe.7105.
Ramalingam, R., Muniyan, R., Dumka, A., Singh, D. P., Mohamed, H. G., Singh, R., ... & Noya, I. D. (2022). Routing Protocol for MANET Based on QoS-Aware Service Composition with Dynamic Secured Broker Selection. Electronics, 11(17), 2637.
Venkatasubramanian, S. (2022, January). Fruit-Fly Algorithm Based Dynamic Source Routing Algorithm for Energy Efficient Multipath Routing in MANET. In 2022 International Conference on Computer Communication and Informatics (ICCCI) (pp. 01-08). IEEE.
Zahid, S., Ullah, K., Waheed, A., Basar, S., Zareei, M., & Biswal, R. R. (2022). Fault Tolerant DHT-Based Routing in MANET. Sensors, 22(11), 4280.
Kumar, M. P., Kumar, M. M., Shobana, S., Padmanaban, L., Nageswaran, A., & Krishnamoorthy, R. (2022, April). Enhanced Secure Routing in MANET using Collaborative Machine Learning Approach. In 2022 8th International Conference on Smart Structures and Systems (ICSSS) (pp. 1-6). IEEE.
DOI: https://doi.org/10.33180/InfMIDEM2024.204
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