4 research outputs found
Traffic Control for Network Protection Against Spreading Processes
Epidemic outbreaks in human populations are facilitated by the underlying
transportation network. We consider strategies for containing a viral spreading
process by optimally allocating a limited budget to three types of protection
resources: (i) Traffic control resources, (ii), preventative resources and
(iii) corrective resources. Traffic control resources are employed to impose
restrictions on the traffic flowing across directed edges in the transportation
network. Preventative resources are allocated to nodes to reduce the
probability of infection at that node (e.g. vaccines), and corrective resources
are allocated to nodes to increase the recovery rate at that node (e.g.
antidotes). We assume these resources have monetary costs associated with them,
from which we formalize an optimal budget allocation problem which maximizes
containment of the infection. We present a polynomial time solution to the
optimal budget allocation problem using Geometric Programming (GP) for an
arbitrary weighted and directed contact network and a large class of resource
cost functions. We illustrate our approach by designing optimal traffic control
strategies to contain an epidemic outbreak that propagates through a real-world
air transportation network.Comment: arXiv admin note: text overlap with arXiv:1309.627
Decentralized Protection Strategies against SIS Epidemics in Networks
Defining an optimal protection strategy against viruses, spam propagation or
any other kind of contamination process is an important feature for designing
new networks and architectures. In this work, we consider decentralized optimal
protection strategies when a virus is propagating over a network through a SIS
epidemic process. We assume that each node in the network can fully protect
itself from infection at a constant cost, or the node can use recovery
software, once it is infected.
We model our system using a game theoretic framework and find pure, mixed
equilibria, and the Price of Anarchy (PoA) in several network topologies.
Further, we propose both a decentralized algorithm and an iterative procedure
to compute a pure equilibrium in the general case of a multiple communities
network. Finally, we evaluate the algorithms and give numerical illustrations
of all our results.Comment: accepted for publication in IEEE Transactions on Control of Network
System