Low Complexity Method for Parent Selection based on Rank Increase Enhancement in RPL routing protocol

Mohammad Koosha, Mina Namdar, Emad Alizadeh
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引用次数: 2

Abstract

6LoWPAN is regarded as the most prominent stack of protocols used for the Internet of Things or IoT and RPL has confirmed itself as the most commonly used network layer protocol for 6LoWPAN. But still, there are dozens of subjects open to research in RPL. One of these issues is the proper route establishment in a network of nodes. This task is preliminarily done by Objective Functions like OF0 and MRHOF. However, these OFs do not seem enough sophisticated since they do not take all the network metrics into consideration and consequently cause fast energy depletion of nodes or poor QoS properties. In this piece of research, we propose a method based on Fuzzy logic to modify the Objective Functions OF0 and MRHOf with regard to almost all the network parameters involved. Then our method is tested and simulated by the Cooja simulator that is based on Contiki OS to prove its effectiveness in comparison to the original OFs. By the results obtained from the simulations we show that our Fuzzy model has helped prolonging the life span of the networks by reducing energy consumption and other network properties like Throughput and PDR have also been improved.
RPL路由协议中基于秩递增的低复杂度父级选择方法
6LoWPAN被认为是用于物联网或IoT的最突出的协议堆栈,RPL已经证实自己是6LoWPAN最常用的网络层协议。但是,在RPL中仍然有几十个课题可供研究。其中一个问题是在节点网络中建立正确的路由。该任务初步由OF0、MRHOF等目标函数完成。然而,这些OFs似乎不够复杂,因为它们没有考虑到所有的网络指标,因此导致节点的快速能量消耗或较差的QoS属性。在本文的研究中,我们提出了一种基于模糊逻辑的方法来修改目标函数OF0和MRHOf,涉及到几乎所有的网络参数。在基于Contiki操作系统的Cooja模拟器上对该方法进行了测试和仿真,验证了该方法与原始OFs相比的有效性。通过仿真得到的结果表明,我们的模糊模型通过降低能耗帮助延长了网络的寿命,并且其他网络特性如吞吐量和PDR也得到了改善。
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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