Francis H. Shajin, Muthusamy Palaniappan, P. Rajesh
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引用次数: 0
摘要
移动特设网络(MANET)路由是一种用于将数据包分配到基站(BS)的有效策略。在路由过程中,恶意节点的出现会影响移动特设网络的运行。因此,需要一种可信的分布式路由协议来维护路由支持和移动特设网络的效率。为了克服这些挑战性问题,本手稿提出了基于区块链技术的自动计量图神经网络,用于城域网中的安全动态优化路由(BC-SDOR-MANET-AGNN)。所提出的方法在 NS-2 工具中进行了仿真。提议的 BC-SDOR-MANET-AGNN 方法在 25% 的恶意路由环境中分别实现了 76.26%、65.57% 和 42.9% 的最小延迟,在 50% 的恶意路由环境中分别实现了 73.06%、63.82% 和 38.84% 的最小延迟。与现有模型相比,如 MANET 的增强型混合安全多路径路由协议(BC-SDOR-MANET-GAHC)、MANET 中基于 BC 技术的改进型 ad hoc on-demand 距离矢量路由安全方法(BC-SDOR-MANET-AODV-MQS)和使用集合算法(BC-SDOR-MANET-E-BATMAN)的基于块链的移动 ad-hoc 网络协议更佳方法。
Auto-metric Graph Neural Network based Blockchain Technology for Secured Dynamic Optimal Routing in MANET
Mobile ad hoc network (MANET) routing is a generous tactic used for allocating packets to the base station (BS). During the operations of routing, occurrence of malicious node embellishes the mobile ad hoc network operations. For that reason, a trusted distributed routing protocol is obliged that maintains the routing buttressing and the proficiency of mobile ad hoc network. To overcome these challenging issues, Auto-Metric Graph Neural Network based Blockchain technology is proposed in this manuscript for Secured Dynamic Optimal Routing in MANET (BC-SDOR-MANET-AGNN). The proposed approach is simulated in NS-2 tool. The proposed BC-SDOR-MANET-AGNN approach attains 76.26%, 65.57%, 42.9% minimal delay during 25% malicious routing environment, 73.06%, 63.82%, 38.84% less delay during 50% malicious routing environment when analyzed to the existing models, like enhanced hybrid secure multipath routing protocol for MANET (BC-SDOR-MANET-GAHC), an improved ad hoc on-demand distance vector routing security approach based on BC technology in MANET (BC-SDOR-MANET-AODV-MQS) and block chain-based better approach for the mobile ad-hoc networking protocol using ensemble algorithm (BC-SDOR-MANET-E-BATMAN) methods.