A Smart Water Metering Deployment Based on the Fog Computing Paradigm
In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, sm...
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MDPI AG
2020-03-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/10/6/1965 |
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author | Dimitrios Amaxilatis Ioannis Chatzigiannakis Christos Tselios Nikolaos Tsironis Nikos Niakas Simos Papadogeorgos |
author_facet | Dimitrios Amaxilatis Ioannis Chatzigiannakis Christos Tselios Nikolaos Tsironis Nikos Niakas Simos Papadogeorgos |
author_sort | Dimitrios Amaxilatis |
collection | DOAJ |
description | In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system’s design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system. |
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id | doaj.art-3cdda62f87ad4b4ca2b23f5b2a42e38c |
institution | Directory Open Access Journal |
issn | 2076-3417 |
language | English |
last_indexed | 2024-12-10T23:09:57Z |
publishDate | 2020-03-01 |
publisher | MDPI AG |
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series | Applied Sciences |
spelling | doaj.art-3cdda62f87ad4b4ca2b23f5b2a42e38c2022-12-22T01:29:58ZengMDPI AGApplied Sciences2076-34172020-03-01106196510.3390/app10061965app10061965A Smart Water Metering Deployment Based on the Fog Computing ParadigmDimitrios Amaxilatis0Ioannis Chatzigiannakis1Christos Tselios2Nikolaos Tsironis3Nikos Niakas4Simos Papadogeorgos5SparkWorks ITC Ltd, Derbyshire DE11 8HS, UKDepartment of Computer, Control and Management Engineering (DIAG), Sapienza University of Rome, 00185 Roma, ItalyDepartment of Electrical and Computer Engineering (ECE), University of Patras, 265 04 Patras, GreeceSparkWorks ITC Ltd, Derbyshire DE11 8HS, UKPower Made SA, 14568 Kryoneri, GreecePower Made SA, 14568 Kryoneri, GreeceIn this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system’s design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system.https://www.mdpi.com/2076-3417/10/6/1965internet of thingssmart sensorssmart actuatorswater meteringsmart gridreal-world deploymentexperimentation |
spellingShingle | Dimitrios Amaxilatis Ioannis Chatzigiannakis Christos Tselios Nikolaos Tsironis Nikos Niakas Simos Papadogeorgos A Smart Water Metering Deployment Based on the Fog Computing Paradigm Applied Sciences internet of things smart sensors smart actuators water metering smart grid real-world deployment experimentation |
title | A Smart Water Metering Deployment Based on the Fog Computing Paradigm |
title_full | A Smart Water Metering Deployment Based on the Fog Computing Paradigm |
title_fullStr | A Smart Water Metering Deployment Based on the Fog Computing Paradigm |
title_full_unstemmed | A Smart Water Metering Deployment Based on the Fog Computing Paradigm |
title_short | A Smart Water Metering Deployment Based on the Fog Computing Paradigm |
title_sort | smart water metering deployment based on the fog computing paradigm |
topic | internet of things smart sensors smart actuators water metering smart grid real-world deployment experimentation |
url | https://www.mdpi.com/2076-3417/10/6/1965 |
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