Title :
Stability properties of infection diffusion dynamics over directed networks
Author :
Khanafer, Ali ; Basar, Tamer ; Gharesifard, Bahman
Author_Institution :
ECE Dept., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
We analyze the stability properties of a susceptible-infected-susceptible diffusion model over directed networks. Similar to the majority of infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the all-healthy state is globally asymptotically stable (GAS). Otherwise, an endemic state arises and the entire network could become infected. Using notions from positive systems theory, we prove that the endemic state is GAS in strongly connected networks. When the graph is weakly connected, we provide conditions for the existence, uniqueness, and global asymptotic stability of weak and strong endemic states. Several simulations demonstrate our results.
Keywords :
asymptotic stability; diffusion; directed graphs; diseases; network theory (graphs); GAS; connected networks; directed networks; global asymptotic stability; infection diffusion dynamics; infection spread dynamics; positive system theory; stability properties; susceptible-infected-susceptible diffusion model; threshold phenomenon; Asymptotic stability; Computational modeling; Curing; Jacobian matrices; Markov processes; Stability analysis; Vectors;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7040363