Pido: Predictive Delay Optimization for Intertidal Wireless Sensor Networks

Intertidal habitats are among the harshest environments on the planet, and have emerged as a model system for exploring the ecological impacts of global climate change. Deploying reliable instrumentation to measure environmental conditions such as temperature is challenging in this environment. The...

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Published in:Sensors (Basel, Switzerland) Vol. 18; no. 5; p. 1464
Main Authors: Zhou, Xinyan, Ji, Xiaoyu, Wang, Bin, Cheng, Yushi, Ma, Zhuoran, Choi, Francis, Helmuth, Brian, Xu, Wenyuan
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 08-05-2018
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Abstract Intertidal habitats are among the harshest environments on the planet, and have emerged as a model system for exploring the ecological impacts of global climate change. Deploying reliable instrumentation to measure environmental conditions such as temperature is challenging in this environment. The application of wireless sensor networks (WSNs) shows considerable promise as a means of optimizing continuous data collection, but poor link quality and unstable connections between nodes, caused by harsh physical environmental conditions, bring about a delay problem. In this paper, we model and analyze the components of delays in an intertidal wireless sensor network system (IT-WSN). We show that, by properly selecting routing pathways, it is feasible to improve delay. To this end, we propose a Predictive Delay Optimization (Pido) framework, which provides a new metric for routing path selection. Pido incorporates delay introduced by both link quality and node conditions, and designs a classifier to predict future conditions of nodes, i.e., the likely time of aerial exposure at low tide in this case. We evaluate the performance of Pido in both a real IT-WSN system and a large-scale simulation, the result demonstrates that Pido decreases up to 73% of delays on average with limited overhead.
AbstractList Intertidal habitats are among the harshest environments on the planet, and have emerged as a model system for exploring the ecological impacts of global climate change. Deploying reliable instrumentation to measure environmental conditions such as temperature is challenging in this environment. The application of wireless sensor networks (WSNs) shows considerable promise as a means of optimizing continuous data collection, but poor link quality and unstable connections between nodes, caused by harsh physical environmental conditions, bring about a delay problem. In this paper, we model and analyze the components of delays in an intertidal wireless sensor network system (IT-WSN). We show that, by properly selecting routing pathways, it is feasible to improve delay. To this end, we propose a Predictive Delay Optimization (Pido) framework, which provides a new metric for routing path selection. Pido incorporates delay introduced by both link quality and node conditions, and designs a classifier to predict future conditions of nodes, i.e., the likely time of aerial exposure at low tide in this case. We evaluate the performance of Pido in both a real IT-WSN system and a large-scale simulation, the result demonstrates that Pido decreases up to 73% of delays on average with limited overhead.
Intertidal habitats are among the harshest environments on the planet, and have emerged as a model system for exploring the ecological impacts of global climate change. Deploying reliable instrumentation to measure environmental conditions such as temperature is challenging in this environment. The application of wireless sensor networks (WSNs) shows considerable promise as a means of optimizing continuous data collection, but poor link quality and unstable connections between nodes, caused by harsh physical environmental conditions, bring about a delay problem. In this paper, we model and analyze the components of delays in an intertidal wireless sensor network system (IT-WSN). We show that, by properly selecting routing pathways, it is feasible to improve delay. To this end, we propose a Predictive Delay Optimization (Pido) framework, which provides a new metric for routing path selection. Pido incorporates delay introduced by both link quality and node conditions, and designs a classifier to predict future conditions of nodes, i.e., the likely time of aerial exposure at low tide in this case. We evaluate the performance of Pido in both a real IT-WSN system and a large-scale simulation, the result demonstrates that Pido decreases up to 73% of delays on average with limited overhead.
Author Cheng, Yushi
Helmuth, Brian
Ji, Xiaoyu
Ma, Zhuoran
Zhou, Xinyan
Xu, Wenyuan
Wang, Bin
Choi, Francis
AuthorAffiliation 1 College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China; xinyanzhou@zju.edu.cn (X.Z.); yushicheng@zju.edu.cn (Y.C.); mzr@zju.edu.cn (Z.M.); wyxu@zju.edu.cn (W.X.)
2 Hangzhou Hikvision Digital Technology Co Ltd., 310051 Hangzhou, China; wangbin2@hikvision.com
3 Department of Marine and Environmental Sciences and School of Public Policy and Urban Affairs, Northeastern University Marine Science Center, Nahant, MA 01908, USA; f.choi@northeastern.edu (F.C.); b.helmuth@northeastern.edu (B.H.)
AuthorAffiliation_xml – name: 3 Department of Marine and Environmental Sciences and School of Public Policy and Urban Affairs, Northeastern University Marine Science Center, Nahant, MA 01908, USA; f.choi@northeastern.edu (F.C.); b.helmuth@northeastern.edu (B.H.)
– name: 1 College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China; xinyanzhou@zju.edu.cn (X.Z.); yushicheng@zju.edu.cn (Y.C.); mzr@zju.edu.cn (Z.M.); wyxu@zju.edu.cn (W.X.)
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Keywords ETX
delay optimization
environmental monitoring
delay modeling
intertidal WSN
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StartPage 1464
SubjectTerms Climate change
Computer simulation
Data acquisition
Delay
delay modeling
delay optimization
Ecological monitoring
Environmental conditions
environmental monitoring
ETX
intertidal WSN
Nodes
Remote sensors
Sensors
Wireless sensor networks
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Title Pido: Predictive Delay Optimization for Intertidal Wireless Sensor Networks
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