Mobility support over RPL using sensor nodes speed classification

Fatma Somaa, I. Korbi, L. Saïdane
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引用次数: 2

Abstract

The interest for wireless sensor networks (WSNs) is continuously growing especially with the emergence of applications such as smart grids, smart cities, e-health, etc. where billions of objets (sensors) will be permanently connected to the Internet. In this context, the IPv6 Routing Protocol for Low power and Lossy Networks (RPL) is placed as the routing standard for the next generation multi-hop WSNs. The RPL scheme fits the sensor nodes characteristics since the protocol was originally designed for energy efficiency. Nevertheless, in the case of sensor nodes' movement, RPL poorly adapts to such scenarios which rapidly alters the network performance. In this paper, we investigate the problem of mobility support over RPL. Therefore, we propose a new Sensor Nodes' Speed Classifier (SNSC) to predict the sensor nodes' movement in the network. Then, we exploit the speed values-predicted by the SNSC model-to enhance the behavior of the native RPL in the mobility context. Our modified RPL scheme is called Mobility Prediction based RPL (MP-RPL). To evaluate the performance of MP-RPL, we first validate the SNSC model using the Cooja/Contiki simulation environment. Then, we compare MP-RPL to the native RPL in terms of Packet Loss Rate (PLR) and Packet Delivery Delay (PDD).
使用传感器节点速度分类的RPL移动支持
对无线传感器网络(wsn)的兴趣不断增长,特别是随着智能电网、智能城市、电子医疗等应用的出现,数十亿物体(传感器)将永久连接到互联网。在这种情况下,IPv6 RPL (Routing Protocol for Low power and Lossy Networks)被作为下一代多跳wsn的路由标准。RPL方案符合传感器节点的特性,因为该协议最初是为了提高能效而设计的。然而,在传感器节点移动的情况下,RPL对这种快速改变网络性能的场景的适应能力较差。本文研究了RPL上的机动性支持问题。因此,我们提出了一种新的传感器节点速度分类器(SNSC)来预测网络中传感器节点的运动。然后,我们利用SNSC模型预测的速度值来增强原生RPL在移动环境中的行为。我们改进的RPL方案被称为基于迁移预测的RPL (MP-RPL)。为了评估MP-RPL的性能,我们首先使用Cooja/Contiki仿真环境验证SNSC模型。然后,我们将MP-RPL与本地RPL在丢包率(PLR)和包传递延迟(PDD)方面进行比较。
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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