Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support
Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infr...
Ausführliche Beschreibung
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| Autor*in: |
Balis Bartosz [verfasserIn] Bartynski Tomasz [verfasserIn] Brzoza-Woch Robert [verfasserIn] Bubak Marian [verfasserIn] Harezlak Daniel [verfasserIn] Kasztelnik Marek [verfasserIn] Konieczny Marek [verfasserIn] Kwolek Bartosz [verfasserIn] Malawski Maciej [verfasserIn] Nawrocki Piotr [verfasserIn] Nowakowski Piotr [verfasserIn] Szydlo Tomasz [verfasserIn] Wilk Bartosz [verfasserIn] Zielinski Krzysztof [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch ; Französisch |
| Erschienen: |
2016 |
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| Übergeordnetes Werk: |
In: E3S Web of Conferences - EDP Sciences, 2013, 7, p 14008(2016) |
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| Übergeordnetes Werk: |
volume:7, p 14008 ; year:2016 |
| Links: |
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| DOI / URN: |
10.1051/e3sconf/20160714008 |
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| Katalog-ID: |
DOAJ053383176 |
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| 520 | |a Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. | ||
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10.1051/e3sconf/20160714008 doi (DE-627)DOAJ053383176 (DE-599)DOAJ9b193622a8eb4c1a9dd7e41c7585be50 DE-627 ger DE-627 rakwb eng fre GE1-350 Balis Bartosz verfasserin aut Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. Environmental sciences Bartynski Tomasz verfasserin aut Brzoza-Woch Robert verfasserin aut Bubak Marian verfasserin aut Harezlak Daniel verfasserin aut Kasztelnik Marek verfasserin aut Konieczny Marek verfasserin aut Kwolek Bartosz verfasserin aut Malawski Maciej verfasserin aut Nawrocki Piotr verfasserin aut Nowakowski Piotr verfasserin aut Szydlo Tomasz verfasserin aut Wilk Bartosz verfasserin aut Zielinski Krzysztof verfasserin aut In E3S Web of Conferences EDP Sciences, 2013 7, p 14008(2016) (DE-627)778372081 (DE-600)2755680-3 22671242 nnns volume:7, p 14008 year:2016 https://doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/article/9b193622a8eb4c1a9dd7e41c7585be50 kostenfrei http://dx.doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/toc/2267-1242 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7, p 14008 2016 |
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10.1051/e3sconf/20160714008 doi (DE-627)DOAJ053383176 (DE-599)DOAJ9b193622a8eb4c1a9dd7e41c7585be50 DE-627 ger DE-627 rakwb eng fre GE1-350 Balis Bartosz verfasserin aut Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. Environmental sciences Bartynski Tomasz verfasserin aut Brzoza-Woch Robert verfasserin aut Bubak Marian verfasserin aut Harezlak Daniel verfasserin aut Kasztelnik Marek verfasserin aut Konieczny Marek verfasserin aut Kwolek Bartosz verfasserin aut Malawski Maciej verfasserin aut Nawrocki Piotr verfasserin aut Nowakowski Piotr verfasserin aut Szydlo Tomasz verfasserin aut Wilk Bartosz verfasserin aut Zielinski Krzysztof verfasserin aut In E3S Web of Conferences EDP Sciences, 2013 7, p 14008(2016) (DE-627)778372081 (DE-600)2755680-3 22671242 nnns volume:7, p 14008 year:2016 https://doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/article/9b193622a8eb4c1a9dd7e41c7585be50 kostenfrei http://dx.doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/toc/2267-1242 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7, p 14008 2016 |
| allfields_unstemmed |
10.1051/e3sconf/20160714008 doi (DE-627)DOAJ053383176 (DE-599)DOAJ9b193622a8eb4c1a9dd7e41c7585be50 DE-627 ger DE-627 rakwb eng fre GE1-350 Balis Bartosz verfasserin aut Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. Environmental sciences Bartynski Tomasz verfasserin aut Brzoza-Woch Robert verfasserin aut Bubak Marian verfasserin aut Harezlak Daniel verfasserin aut Kasztelnik Marek verfasserin aut Konieczny Marek verfasserin aut Kwolek Bartosz verfasserin aut Malawski Maciej verfasserin aut Nawrocki Piotr verfasserin aut Nowakowski Piotr verfasserin aut Szydlo Tomasz verfasserin aut Wilk Bartosz verfasserin aut Zielinski Krzysztof verfasserin aut In E3S Web of Conferences EDP Sciences, 2013 7, p 14008(2016) (DE-627)778372081 (DE-600)2755680-3 22671242 nnns volume:7, p 14008 year:2016 https://doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/article/9b193622a8eb4c1a9dd7e41c7585be50 kostenfrei http://dx.doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/toc/2267-1242 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7, p 14008 2016 |
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10.1051/e3sconf/20160714008 doi (DE-627)DOAJ053383176 (DE-599)DOAJ9b193622a8eb4c1a9dd7e41c7585be50 DE-627 ger DE-627 rakwb eng fre GE1-350 Balis Bartosz verfasserin aut Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. Environmental sciences Bartynski Tomasz verfasserin aut Brzoza-Woch Robert verfasserin aut Bubak Marian verfasserin aut Harezlak Daniel verfasserin aut Kasztelnik Marek verfasserin aut Konieczny Marek verfasserin aut Kwolek Bartosz verfasserin aut Malawski Maciej verfasserin aut Nawrocki Piotr verfasserin aut Nowakowski Piotr verfasserin aut Szydlo Tomasz verfasserin aut Wilk Bartosz verfasserin aut Zielinski Krzysztof verfasserin aut In E3S Web of Conferences EDP Sciences, 2013 7, p 14008(2016) (DE-627)778372081 (DE-600)2755680-3 22671242 nnns volume:7, p 14008 year:2016 https://doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/article/9b193622a8eb4c1a9dd7e41c7585be50 kostenfrei http://dx.doi.org/10.1051/e3sconf/20160714008 kostenfrei https://doaj.org/toc/2267-1242 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7, p 14008 2016 |
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Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. |
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Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. |
| abstract_unstemmed |
Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation. |
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| title_short |
Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support |
| url |
https://doi.org/10.1051/e3sconf/20160714008 https://doaj.org/article/9b193622a8eb4c1a9dd7e41c7585be50 http://dx.doi.org/10.1051/e3sconf/20160714008 https://doaj.org/toc/2267-1242 |
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Bartynski Tomasz Brzoza-Woch Robert Bubak Marian Harezlak Daniel Kasztelnik Marek Konieczny Marek Kwolek Bartosz Malawski Maciej Nawrocki Piotr Nowakowski Piotr Szydlo Tomasz Wilk Bartosz Zielinski Krzysztof |
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Bartynski Tomasz Brzoza-Woch Robert Bubak Marian Harezlak Daniel Kasztelnik Marek Konieczny Marek Kwolek Bartosz Malawski Maciej Nawrocki Piotr Nowakowski Piotr Szydlo Tomasz Wilk Bartosz Zielinski Krzysztof |
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| doi_str |
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