2 research outputs found
Clearing Contamination in Large Networks
In this work, we study the problem of clearing contamination spreading
through a large network where we model the problem as a graph searching game.
The problem can be summarized as constructing a search strategy that will leave
the graph clear of any contamination at the end of the searching process in as
few steps as possible. We show that this problem is NP-hard even on directed
acyclic graphs and provide an efficient approximation algorithm. We
experimentally observe the performance of our approximation algorithm in
relation to the lower bound on several large online networks including
Slashdot, Epinions and Twitter. The experiments reveal that in most cases our
algorithm performs near optimally