Abstract
Knowledge on the dynamics of standard epidemic models and their variants over complex networks has been well-established primarily in the stationary regime, with relatively little light shed on their transient behavior. In this paper, we analyze the transient characteristics of the classical susceptible-infected (SI) process with a recovery policy modeled as a state-dependent retrial queueing system in which arriving infected nodes, upon finding all the limited number of recovery units busy, join a virtual buffer and try persistently for service in order to regain susceptibility. In particular, we formulate the stochastic SI epidemic model with added retrial phenomenon as a finite continuous-time Markov chain (CTMC) and derive the Laplace transforms of the underlying transient state probability distributions and corresponding moments for a closed population of size N driven by homogeneous and heterogeneous contacts. Our numerical results reveal the strong influence of infection heterogeneity and retrial frequency on the transient behavior of the model for various performance measures.
Original language | English |
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Title of host publication | 37th IEEE Sarnoff Symposium, Sarnoff 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 187-192 |
Number of pages | 6 |
ISBN (Electronic) | 9781509015405 |
DOIs | |
Publication status | Published - Feb 7 2017 |
Externally published | Yes |
Event | 37th IEEE Sarnoff Symposium, Sarnoff 2016 - Newark, United States Duration: Sep 19 2016 → Sep 21 2016 |
Conference
Conference | 37th IEEE Sarnoff Symposium, Sarnoff 2016 |
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Country | United States |
City | Newark |
Period | 9/19/16 → 9/21/16 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture