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一种用于无线传感器网络中连续对象的节能汇聚节点定位服务。

An Energy Efficient Sink Location Service for Continuous Objects in Wireless Sensor Networks.

作者信息

Kim Cheonyong, Kim Sangdae, Cho Hyunchong, Kim Sangha, Oh Seungmin

机构信息

Advanced KREONET Center, Korea Institute of Science and Technology Information, Daejeon 34141, Korea.

Division of Computer Science and Engineering, Kongju National University, Cheonan 31080, Korea.

出版信息

Sensors (Basel). 2020 Dec 18;20(24):7282. doi: 10.3390/s20247282.

DOI:10.3390/s20247282
PMID:33353141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7766020/
Abstract

In wireless sensor networks (WSNs), detection and report of continuous object, such as forest fire and toxic gas leakage, is one of the major applications. In large-scale continuous object tracking in WSNs, there might be many source nodes simultaneously, detecting the continuous object. Each nodes reports its data to both a base station and mobile workers in the industry field. For communication between the source nodes and a mobile worker, sink location service is needed to continuously notify the location of the mobile worker. But, as the application has a large number of sources, it causes a waste of energy consumption. To address this issue, in this paper, we propose a two-phase sink location service scheme. In the first phase, the proposed scheme constructs a virtual grid structure for merging the source nodes. Then, the proposed scheme aggregates the merging points from an originated merging point as the second phase. Simulation results show that the proposed scheme is superior to other schemes in terms of energy consumption.

摘要

在无线传感器网络(WSN)中,对森林火灾和有毒气体泄漏等连续对象的检测与报告是主要应用之一。在WSN的大规模连续对象跟踪中,可能会有多个源节点同时检测连续对象。每个节点都要将其数据报告给基站和工业领域的移动工作人员。为了在源节点和移动工作人员之间进行通信,需要下沉位置服务来持续通知移动工作人员的位置。但是,由于该应用有大量的源,这会导致能源消耗的浪费。为了解决这个问题,在本文中,我们提出了一种两阶段下沉位置服务方案。在第一阶段,该方案构建一个虚拟网格结构来合并源节点。然后,作为第二阶段,该方案从起始合并点聚合合并点。仿真结果表明,该方案在能源消耗方面优于其他方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/d8d62e4de7fc/sensors-20-07282-g018.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/d8d62e4de7fc/sensors-20-07282-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/e9056f76760a/sensors-20-07282-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/e520cea5c8b5/sensors-20-07282-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/84cd53b52110/sensors-20-07282-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/e48a3b843fe5/sensors-20-07282-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/978c19faac57/sensors-20-07282-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/8f5715b625c8/sensors-20-07282-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/f2e9af32a463/sensors-20-07282-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/044b42eb6bbb/sensors-20-07282-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/1fe816f08a14/sensors-20-07282-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/36172466f2e8/sensors-20-07282-g016.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b2/7766020/d8d62e4de7fc/sensors-20-07282-g018.jpg

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Sensors (Basel). 2017 Feb 13;17(2):361. doi: 10.3390/s17020361.