Abstract
Mobile Adhoc network (MANET) is a wireless and infrastructure less network where nodes may behave non cooperative due to limited resource constraint. In this paper a node cooperation enforcement scheme assess the node’s trust with respect to multiple parameters namely packet forwarding potential, node energy, throughput, delay. In MANETs due to the node’s limited resource nature and frequent and unpredictable network topology, it is not suffice to consider node’s current trust also it is required to consider nodes previous behavior for which in this paper a predictive model used to decide the node is trusted or not. The proposed Machine Learning based Node Cooperation Enforcement Scheme (MLNCES) performance is analyzed experimentally. In simulation results, the proposed method MLNCES outperforms the FCOPRAS-NCETE and GTF-GDMT approaches.
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Sirisala, S., Rajeswarappa, G., Lakumarapu, S. (2023). Node Cooperation Enforcement Scheme for Enhancing Quality of Service in MANETs Using Machine Learning Approach. In: Morusupalli, R., Dandibhotla, T.S., Atluri, V.V., Windridge, D., Lingras, P., Komati, V.R. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2023. Lecture Notes in Computer Science(), vol 14078. Springer, Cham. https://doi.org/10.1007/978-3-031-36402-0_32
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