Robust distributed routing in dynamical networks with cascading failures
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Frazzoli_Robust distributed.pdf
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Author(s)
Como, Giacomo
Acemoglu, Daron
Dahleh, Munther A.
Frazzoli, Emilio
Savla, Ketan D.
Date Issued
December 2012
Journal
Proceedings of the 2012 51st IEEE Conference on Decision and Control (CDC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Como, Giacomo, Ketan Savla, Daron Acemoglu, Munther A. Dahleh, and Emilio Frazzoli. “Robust distributed routing in dynamical networks with cascading failures.” In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 7413-7418. Institute of Electrical and Electronics Engineers, 2012.
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Author's final manuscript
Abstract
We consider a dynamical formulation of network flows, whereby the network is modeled as a switched system of ordinary differential equations derived from mass conservation laws on directed graphs with a single origin-destination pair and a constant inflow at the origin. The rate of change of the density on each link of the network equals the difference between the inflow and the outflow on that link. The inflow to a link is determined by the total flow arriving to the tail node of that link and the routing policy at that tail node. The outflow from a link is modeled to depend on the current density on that link through a flow function. Every link is assumed to have finite capacity for density and the flow function is modeled to be strictly increasing up to the maximum density. A link becomes inactive when the density on it reaches the capacity. A node fails if all its outgoing links become inactive, and such node failures can propagate through the network due to rerouting of flow. We prove some properties of these dynamical networks and study the resilience of such networks under distributed routing policies with respect to perturbations that reduce link-wise flow functions. In particular, we propose an algorithm to compute upper bounds on the maximum resilience over all distributed routing policies, and discuss examples that highlight the role of cascading failures on the resilience of the network.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Economics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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DOI of Published Version
https://doi.org/10.1109/CDC.2012.6426170
