低功耗损耗网络中路由协议的性能评估

Hanane Lamaazi, N. Benamar, M. Imaduddin, A. Jara
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引用次数: 30

摘要

RPL (IPv6 Routing Protocol for Low Power and Lossy Networks)是由IETF的ROLL工作组提出的。物联网中使用的该协议最适合低功耗和有损网络(lln)。但是,在网络密度较大的情况下,RPL网络存在一定的局限性。在本文中,我们评估了RPL在三种不同场景下的性能。首先,我们评估了具有固定节点的RPL的特性(一个接收节点和其他发送节点)。然后我们加入移动性,并将移动节点与固定节点进行比较,以显示移动性如何影响协议参数。最后,我们研究了RPL在网络密度较大时的行为,以评估协议的性能。在本研究中,我们使用Contiki OS和Cooja软件进行所有模拟。结果表明,RPL性能受节点数量、移动类型和网络拓扑结构的影响较大。当节点数量增加时,所有指标也会增加,特别是功耗,直到增加52,85%。此外,随机路径点移动模型(RWP)在跳数和期望传输(ETX)值方面提供了比随机行走(RWK)移动模型更好的指标。在RWP模型中,节点功耗比RWK模型低10.73%。我们的模拟清楚地表明,功耗与网络中汇聚节点的数量直接相关。这种类型的节点在网络中出现的越多,所消耗的功率就越少。功率下降可能会持续到5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance assessment of the routing protocol for low power and lossy networks
RPL (IPv6 Routing Protocol for Low Power and Lossy Networks) is proposed by the ROLL working group at IETF. This protocol used in the Internet of Things is optimal for Low power and Lossy Networks (LLNs). However, the RPL network has some limits when the network is dense. In this paper we evaluate the performance of RPL in three different scenarios. We first, evaluate the characteristics of RPL with fixed nodes, (one sink and others are senders). Then we add mobility, and we compare mobile nodes to fixed nodes in order to show how mobility can influence protocol parameters. Finally, we study the behavior of RPL when the network is dense in order to assess the protocol performances. In this study, we use Contiki OS and Cooja software for all simulations. The results show that RPL performances are greatly influenced by the number of nodes, type of mobility and the topology of the network. When the number of nodes increases, all metrics increase too, especially the power consumption which arrives until an augmentation of 52,85%. Furthermore, Random Waypoint Mobility Model (RWP) gives better metrics than Random Walk (RWK) Mobility Model in terms of number of hops and Expected Transmission (ETX) value. Also, in RWP model, nodes consume 10,73% of power than RWK. Our simulations show clearly that the power consumption is directly related to the number of sink nodes in the network. The more this type of node is present in the network the less power is consumed. The power reduction may occur till 5%.
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