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首页> 外文期刊>International Journal of Fuzzy Systems >An Energy-Efficient Routing Approach for Performance Enhancement of MANET Through Adaptive Neuro-Fuzzy Inference System
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An Energy-Efficient Routing Approach for Performance Enhancement of MANET Through Adaptive Neuro-Fuzzy Inference System

机译:通过自适应神经模糊推理系统增强MANET性能的节能路由方法

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摘要

Mobile ad hoc network comprises of wireless nodes which are mobile in nature and have short lifespan. They join together to create a self-configured infrastructure-less network where routing is an important challenge. In AODV routing, the hello messages are broadcast periodically by nodes for monitoring the link connectivity to neighbors and for maintaining routing table. The broadcasting of hello messages increases when link failure occurs due to node mobility, which leads to higher consumption of node energy and increases overhead within network. This paper proposes an energy-efficient routing approach (EE-RA), which calculates optimal hello interval for reducing the unnecessary broadcasting of hello messages that further reduces node's energy consumption and network overhead. This is achieved by using Mamdani-based fuzzy inference system and adaptive neuro-fuzzy inference system (ANFIS) to calculate the resultant optimal hello interval in which energy and mobility of node are taken as inputs. Moreover, simulation results illustrate that the performance of EE-RA outperforms AODV and achieve better results for ANFIS in hello message fraction, network overhead, average energy consumption, packet delivery ratio, end-to-end delay and throughput, especially in highly mobile and dense environment.
机译:移动自组织网络包括本质上是移动的且寿命短的无线节点。他们共同创建了一个自配置的,无需基础架构的网络,而路由是一个重要的挑战。在AODV路由中,hello消息由节点定期广播,以监视与邻居的链接连接并维护路由表。当由于节点移动性而发生链路故障时,hello消息的广播会增加,这会导致节点能量的更高消耗并增加网络内的开销。本文提出了一种节能路由方法(EE-RA),该方法可计算最佳问候间隔以减少不必要的问候消息广播,从而进一步减少节点的能耗和网络开销。这是通过使用基于Mamdani的模糊推理系统和自适应神经模糊推理系统(ANFIS)计算所得的最佳hello间隔来实现的,其中节点的能量和移动性作为输入。此外,仿真结果表明,EE-RA的性能优于AODV,并且在问候消息分数,网络开销,平均能耗,数据包传递率,端到端延迟和吞吐量方面,特别是在高度移动和高可用性环境中,其ANFIS效果更好。密集的环境。

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