This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everything (IoE) and the new trend of the Connected Community (CC). A conceptual extension of Functional Resonance Analysis Method (FRAM) and its formalization have been proposed and used to model UTS complexity. The scope is to identify the system functions and their interdependencies with a particular focus on those that have a relation and impact on people and communities. Network analysis techniques have been applied to the FRAM model to identify and estimate the most critical community-related functions. The notion of Variability Rate (VR) has been defined as the amount of output variability generated by an upstream function that can be tolerated/absorbed by a downstream function, without significantly increasing of its subsequent output variability. A fuzzybased quantification of the VR based on expert judgment has been developed when quantitative data are not available. Our approach has been applied to a critical scenario as flash flooding considering two cases: when UTS has CC and IoE implemented or not. However, the method can be applied in different scenarios and critical infrastructures. The results show a remarkable VR enhancement if CC and IoE are deployed.

Quantify resilience enhancement of UTS through exploiting connected community and internet of everything emerging technologies / B. Emanuele, P. Ceravolo, N. Paolo. - In: ACM TRANSACTIONS ON INTERNET TECHNOLOGY. - ISSN 1533-5399. - 18:1(2017), pp. 7.1-7.34. [10.1145/3137572]

Quantify resilience enhancement of UTS through exploiting connected community and internet of everything emerging technologies

P. Ceravolo
Co-primo
Membro del Collaboration Group
;
2017

Abstract

This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everything (IoE) and the new trend of the Connected Community (CC). A conceptual extension of Functional Resonance Analysis Method (FRAM) and its formalization have been proposed and used to model UTS complexity. The scope is to identify the system functions and their interdependencies with a particular focus on those that have a relation and impact on people and communities. Network analysis techniques have been applied to the FRAM model to identify and estimate the most critical community-related functions. The notion of Variability Rate (VR) has been defined as the amount of output variability generated by an upstream function that can be tolerated/absorbed by a downstream function, without significantly increasing of its subsequent output variability. A fuzzybased quantification of the VR based on expert judgment has been developed when quantitative data are not available. Our approach has been applied to a critical scenario as flash flooding considering two cases: when UTS has CC and IoE implemented or not. However, the method can be applied in different scenarios and critical infrastructures. The results show a remarkable VR enhancement if CC and IoE are deployed.
Functional Resonance Analysis Method; Fuzzy Logic; Resilience; Computer Networks and Communications
Settore INF/01 - Informatica
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/531162
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