Consider a network of k servers and their users. Each server provides a unique service that has a certain utility for each user. Now comes an attacker who wishes to destroy a set of network edges to maximize his net g...
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Consider a network of k servers and their users. Each server provides a unique service that has a certain utility for each user. Now comes an attacker who wishes to destroy a set of network edges to maximize his net gain, namely the total disconnected utilities of the users minus the total edge-destruction cost. This k-server disconnection problem is NP-hard and, furthermore, cannot be approximated within a polynomially computable factor of the optimum when k is part of the input. Even for any fixed k >= 2, there is a constant epsilon > 0 such that approximation of the problem within a factor 1/(1 + epsilon) of the optimum is NP-hard. However, a (1/2 + 1/2(k+1)-2)-approximation can be created in the time of 0(2 k) applications of a min-cut algorithm. The main idea is to approximate the optimum with special solutions computable in polynomial time due to supermodularity. Therefore, when the the network has, as is usual in most cases, only a few servers, a 0.5-approximation can be carried out in polynomial time. (c) 2007 Wiley Periodicals, Inc.
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