NNRA-CAC: NARX Neural Network-based Rate Adjustment for Congestion Avoidance and Control in Wireless Sensor Networks

Q2 Social Sciences

New Review of Information Networking Pub Date : 2017-07-03 DOI:10.1080/13614576.2017.1368407

Dr. Vaibhav Eknath Narawade, U. Kolekar

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引用次数: 3

Abstract

ABSTRACT A wireless sensor network (WSN) is an application area that is valuable in various fields, such as healthcare monitoring, environmental monitoring, and so on. Application areas require WSNs with high throughput and low degree of packet loss. Due to congestion in the network, the throughput of the network is affected, which imposes the need for congestion control in the network. This article proposes a method, titled NARX Neural network-based Rate Adjustment (NNRA) for avoiding and controlling congestion in the network. Initially, congestion in the network is avoided by dropping packets and the NNRA is used to control congestion in the network when congestion is present. Performance analysis is carried out in terms of throughput, delay, size of the queue, packet loss, and the level of the congestion using two setups. The results of the proposed method are compared with the existing methods to prove the effectiveness of the proposed method. The proposed method attained a maximum throughput at a rate of 0.9585 and minimum values for delay, queue size, packet loss, and the congestion level.

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NNRA-CAC:基于NARX神经网络的无线传感器网络拥塞避免与控制速率调整

摘要无线传感器网络（WSN）是一个在医疗监测、环境监测等各个领域都很有价值的应用领域。应用领域要求无线传感器网络具有高吞吐量和低丢包率。由于网络中的拥塞，网络的吞吐量受到影响，这就要求在网络中进行拥塞控制。本文提出了一种基于NARX神经网络的速率调整（NNRA）方法来避免和控制网络中的拥塞。最初，通过丢弃数据包来避免网络中的拥塞，并且当存在拥塞时，NNRA用于控制网络中的阻塞。性能分析是根据吞吐量、延迟、队列大小、数据包丢失和使用两种设置的拥塞程度进行的。将所提出的方法的结果与现有方法进行了比较，以证明所提出方法的有效性。所提出的方法以0.9585的速率获得了最大吞吐量，并获得了延迟、队列大小、分组丢失和拥塞级别的最小值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

New Review of Information Networking Social Sciences-Education

CiteScore

2.10

自引率

0.00%

发文量

期刊介绍： Information networking is an enabling technology with the potential to integrate and transform information provision, communication and learning. The New Review of Information Networking, published biannually, provides an expert source on the needs and behaviour of the network user; the role of networks in teaching, learning, research and scholarly communication; the implications of networks for library and information services; the development of campus and other information strategies; the role of information publishers on the networks; policies for funding and charging for network and information services; and standards and protocols for network applications.