TY - JOUR
T1 - Resilience of IoT Systems Against Edge-Induced Cascade-of-Failures
T2 - A Networking Perspective
AU - Wang, Jie
AU - Pambudi, Sigit
AU - Wang, Wenye
AU - Song, Min
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Internet of Things (IoT) is a networking paradigm that interconnects physical systems to the cyber world, to provide automation and intelligence via interdependent links between the two domains. Such interdependence renders IoT systems vulnerable to random failures, e.g., broken communication links or crashed cyber instances, because a single incident in one domain can develop into a cascade-of-failures across domains, which dissolves the network structure, and has devastating consequences. To answer how robust an IoT system is, this paper studies its resilience by examining the impact of edge- and jointly-induced cascades, that is, a sequence of failures caused by randomly broken physical links (and simultaneous failing cyber nodes). Resilience of an IoT system is quantified by two new metrics, the critical edge disconnecting probability \phi -{cr} , i.e., the maximum intensity of random failures the system can withstand, and the cascade length \tau -{cf} , i.e., the lifetime of a cascade. For IoT systems with Poisson degree distributions, we derive exact solutions for the critical disconnecting probability \phi -{cr} , above which an edge-induced cascade will completely fragment the network. We also find that the critical condition \phi -{cr} marks a dichotomy of the expected cascade length \mathbb {E}(\tau -{cf}) : for the super-critical ( \phi > \phi -{cr} ) scenario, we obtain \mathbb {E}(\tau -{cf}) \sim \exp (1-\phi) through analysis, while for the subcritical scenario, we observe \mathbb {E}(\tau -{cf}) \sim \exp (1/1-\phi) through simulations. With these results, the final outcome of a cascade can be anticipated upon the initial failures, while the reaction window of time-sensitive countermeasures can be obtained before a cascade fully unfolds.
AB - Internet of Things (IoT) is a networking paradigm that interconnects physical systems to the cyber world, to provide automation and intelligence via interdependent links between the two domains. Such interdependence renders IoT systems vulnerable to random failures, e.g., broken communication links or crashed cyber instances, because a single incident in one domain can develop into a cascade-of-failures across domains, which dissolves the network structure, and has devastating consequences. To answer how robust an IoT system is, this paper studies its resilience by examining the impact of edge- and jointly-induced cascades, that is, a sequence of failures caused by randomly broken physical links (and simultaneous failing cyber nodes). Resilience of an IoT system is quantified by two new metrics, the critical edge disconnecting probability \phi -{cr} , i.e., the maximum intensity of random failures the system can withstand, and the cascade length \tau -{cf} , i.e., the lifetime of a cascade. For IoT systems with Poisson degree distributions, we derive exact solutions for the critical disconnecting probability \phi -{cr} , above which an edge-induced cascade will completely fragment the network. We also find that the critical condition \phi -{cr} marks a dichotomy of the expected cascade length \mathbb {E}(\tau -{cf}) : for the super-critical ( \phi > \phi -{cr} ) scenario, we obtain \mathbb {E}(\tau -{cf}) \sim \exp (1-\phi) through analysis, while for the subcritical scenario, we observe \mathbb {E}(\tau -{cf}) \sim \exp (1/1-\phi) through simulations. With these results, the final outcome of a cascade can be anticipated upon the initial failures, while the reaction window of time-sensitive countermeasures can be obtained before a cascade fully unfolds.
KW - Interdependent networks
KW - Internet of Things (IoT) architecture
KW - network resilience
UR - http://www.scopus.com/inward/record.url?scp=85070204909&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070204909&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2019.2913140
DO - 10.1109/JIOT.2019.2913140
M3 - Article
AN - SCOPUS:85070204909
VL - 6
SP - 6952
EP - 6963
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 4
M1 - 8698298
ER -