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Use of Model-Based Design Methods fo...
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Knox, Lenora A.
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Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles./
作者:
Knox, Lenora A.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
154 p.
附註:
Source: Dissertation Abstracts International, Volume: 78-09(E), Section: B.
Contained By:
Dissertation Abstracts International78-09B(E).
標題:
Systems science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10265223
ISBN:
9781369705713
Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles.
Knox, Lenora A.
Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 154 p.
Source: Dissertation Abstracts International, Volume: 78-09(E), Section: B.
Thesis (D.Engr.)--The George Washington University, 2017.
The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.
ISBN: 9781369705713Subjects--Topical Terms:
3168411
Systems science.
Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles.
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The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.
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