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一种基于RPL的AMI无线传感器网络功率规划算法

A Power Planning Algorithm Based on RPL for AMI Wireless Sensor Networks.

作者信息

Miguel Marcio L F, Jamhour Edgard, Pellenz Marcelo E, Penna Manoel C

机构信息

PPGIa, Pontifical Catholic University of Parana-Parana, Curitiba 80215-901, Brazil.

出版信息

Sensors (Basel). 2017 Mar 25;17(4):679. doi: 10.3390/s17040679.

DOI:10.3390/s17040679
PMID:28346339
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5419792/
Abstract

The advanced metering infrastructure (AMI) is an architecture for two-way communication between electric, gas and water meters and city utilities. The AMI network is a wireless sensor network that provides communication for metering devices in the neighborhood area of the smart grid. Recently, the applicability of a routing protocol for low-power and lossy networks (RPL) has been considered in AMI networks. Some studies in the literature have pointed out problems with RPL, including sub-optimal path selection and instability. In this paper, we defend the viewpoint that careful planning of the transmission power in wireless RPL networks can significantly reduce the pointed problems. This paper presents a method for planning the transmission power in order to assure that, after convergence, the size of the parent set of the RPL nodes is as close as possible to a predefined size. Another important feature is that all nodes in the parent set offer connectivity through links of similar quality.

摘要

先进计量基础设施（AMI）是一种用于电表、气表和水表与城市公用事业之间双向通信的架构。AMI网络是一种无线传感器网络，为智能电网邻域内的计量设备提供通信。最近，低功耗有损网络（RPL）路由协议在AMI网络中的适用性受到了关注。文献中的一些研究指出了RPL存在的问题，包括次优路径选择和不稳定性。在本文中，我们支持这样一种观点，即对无线RPL网络中的传输功率进行精心规划可以显著减少上述问题。本文提出了一种规划传输功率的方法，以确保在收敛后，RPL节点父集的大小尽可能接近预定义大小。另一个重要特性是，父集中的所有节点都通过质量相似的链路提供连接性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/8b2b35bc770a/sensors-17-00679-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/aeb0a2a61a80/sensors-17-00679-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/4a545af40efb/sensors-17-00679-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/4950643e768f/sensors-17-00679-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/8ddf21d33166/sensors-17-00679-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/c83816989b4d/sensors-17-00679-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/cca433ed7572/sensors-17-00679-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/fcb1c0f6cb31/sensors-17-00679-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/267e6adb10ae/sensors-17-00679-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/f5305e5b04b2/sensors-17-00679-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/8b2b35bc770a/sensors-17-00679-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/aeb0a2a61a80/sensors-17-00679-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/4a545af40efb/sensors-17-00679-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/4950643e768f/sensors-17-00679-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/8ddf21d33166/sensors-17-00679-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/c83816989b4d/sensors-17-00679-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/cca433ed7572/sensors-17-00679-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/fcb1c0f6cb31/sensors-17-00679-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/267e6adb10ae/sensors-17-00679-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/f5305e5b04b2/sensors-17-00679-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b18/5419792/8b2b35bc770a/sensors-17-00679-g010.jpg

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A Proposal for IoT Dynamic Routes Selection Based on Contextual Information.基于上下文信息的物联网动态路由选择方案
Sensors (Basel). 2018 Jan 26;18(2):353. doi: 10.3390/s18020353.