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 |
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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. |
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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.) – name: 2 Hangzhou Hikvision Digital Technology Co Ltd., 310051 Hangzhou, China; wangbin2@hikvision.com |
Author_xml | – sequence: 1 givenname: Xinyan orcidid: 0000-0003-1368-8839 surname: Zhou fullname: Zhou, Xinyan email: xinyanzhou@zju.edu.cn organization: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China. xinyanzhou@zju.edu.cn – sequence: 2 givenname: Xiaoyu surname: Ji fullname: Ji, Xiaoyu email: xji@zju.edu.cn organization: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China. xji@zju.edu.cn – sequence: 3 givenname: Bin surname: Wang fullname: Wang, Bin email: wangbin2@hikvision.com organization: Hangzhou Hikvision Digital Technology Co Ltd., 310051 Hangzhou, China. wangbin2@hikvision.com – sequence: 4 givenname: Yushi surname: Cheng fullname: Cheng, Yushi email: yushicheng@zju.edu.cn organization: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China. yushicheng@zju.edu.cn – sequence: 5 givenname: Zhuoran surname: Ma fullname: Ma, Zhuoran email: mzr@zju.edu.cn organization: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China. mzr@zju.edu.cn – sequence: 6 givenname: Francis surname: Choi fullname: Choi, Francis email: f.choi@northeastern.edu organization: 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 – sequence: 7 givenname: Brian orcidid: 0000-0003-0180-3414 surname: Helmuth fullname: Helmuth, Brian email: b.helmuth@northeastern.edu organization: Department of Marine and Environmental Sciences and School of Public Policy and Urban Affairs, Northeastern University Marine Science Center, Nahant, MA 01908, USA. b.helmuth@northeastern.edu – sequence: 8 givenname: Wenyuan surname: Xu fullname: Xu, Wenyuan email: wyxu@zju.edu.cn organization: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China. wyxu@zju.edu.cn |
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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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