A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink

Wireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot pr...

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Main Authors: Chuan Zhu, Shuai Wu, Guangjie Han, Lei Shu, Hongyi Wu
Format: Article
Language:English
Published: IEEE 2015-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7091856/
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spelling doaj-ae62b5d4f1d54820a267374efab355402021-03-29T19:33:07ZengIEEEIEEE Access2169-35362015-01-01338139610.1109/ACCESS.2015.24244527091856A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile SinkChuan Zhu0Shuai Wu1Guangjie Han2https://orcid.org/0000-0002-6921-7369Lei Shu3Hongyi Wu4Department of Information and Communication Systems, Hohai University, Changzhou, ChinaDepartment of Information and Communication Systems, Hohai University, Changzhou, ChinaDepartment of Information and Communication Systems, Hohai University, Changzhou, ChinaGuangdong Petrochemical Equipment Fault Diagnosis Key Laboratory, Guangdong University of Petrochemical Technology, Maoming, China University of Louisiana at Lafayette, Lafayette, LA, USAWireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot problem affects the network connectivity and decreases the network lifetime. Hence, we propose a tree-cluster-based data-gathering algorithm (TCBDGA) for WSNs with a mobile sink. A novel weight-based tree-construction method is introduced. The root nodes of the constructed trees are defined as rendezvous points (RPs). Additionally, some special nodes called subrendezvous points (SRPs) are selected according to their traffic load and hops to root nodes. RPs and SRPs are viewed as stop points of the mobile sink for data collection, and can be reselected after a certain period. The simulation and comparison with other algorithms show that our TCBDGA can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime.https://ieeexplore.ieee.org/document/7091856/data gathering schemeclustermobile sinkwireless sensor networks
collection DOAJ
language English
format Article
sources DOAJ
author Chuan Zhu
Shuai Wu
Guangjie Han
Lei Shu
Hongyi Wu
spellingShingle Chuan Zhu
Shuai Wu
Guangjie Han
Lei Shu
Hongyi Wu
A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink
IEEE Access
data gathering scheme
cluster
mobile sink
wireless sensor networks
author_facet Chuan Zhu
Shuai Wu
Guangjie Han
Lei Shu
Hongyi Wu
author_sort Chuan Zhu
title A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink
title_short A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink
title_full A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink
title_fullStr A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink
title_full_unstemmed A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink
title_sort tree-cluster-based data-gathering algorithm for industrial wsns with a mobile sink
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2015-01-01
description Wireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot problem affects the network connectivity and decreases the network lifetime. Hence, we propose a tree-cluster-based data-gathering algorithm (TCBDGA) for WSNs with a mobile sink. A novel weight-based tree-construction method is introduced. The root nodes of the constructed trees are defined as rendezvous points (RPs). Additionally, some special nodes called subrendezvous points (SRPs) are selected according to their traffic load and hops to root nodes. RPs and SRPs are viewed as stop points of the mobile sink for data collection, and can be reselected after a certain period. The simulation and comparison with other algorithms show that our TCBDGA can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime.
topic data gathering scheme
cluster
mobile sink
wireless sensor networks
url https://ieeexplore.ieee.org/document/7091856/
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