基于机器学习技术的manet路由算法性能评价

Duraipandian M Dr
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引用次数: 59

摘要

无线通信技术的飞速发展导致了自组网的非凡发展。移动自组织网络是自组织网络的一个子类,它几乎具有自组织网络的相同特征,在构建从源到目的的信息传输路由时提出了多重挑战。为此,本文提出了一种基于强化学习的路由方法,利用节点信息建立一条短而稳定的路由。提出的方法能够最大限度地降低能耗和传输延迟,提高数据包的投递率,提高吞吐量。通过在网络模拟器ii中验证该方法的性能,从能耗、传输延迟和包投递率三个方面来确定该方法的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PERFORMANCE EVALUATION OF ROUTING ALGORITHM FOR MANET BASED ON THE MACHINE LEARNING TECHNIQUES
The rapid advances in wireless communication technology has led to an extraordinary progress in the adhoc type of networking. The mobile adhoc networks being a subtype of the adhoc network almost poses the same characteristics of the adhoc network, presenting multiple challenges in framing a route for the transmission of the information from the source to the destination. So the paper proposes a routing method developed based on the reinforcement learning, exploiting the node information’s to establish a route that is short and stable. The proposed method scopes to minimize the energy consumption, transmission delay, and improve the delivery ratio of the packets, enhancing the throughput. The efficiency of the proposed method is determined by validating its performance in the network simulator-II, in terms of the energy consumption, delay in the transmission and the packet delivery ratio.
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