fault identification using end-to-end data by imperialist competitive algorithm

faults in computer networks may result in millions of dollars in cost. faults in a network need to be localized and repaired to keep the health of the network. fault management systems are used to keep today’s complex networks running without significant cost, either by using active techniques or passive techniques. in this paper, we propose a novel approach based on imperialist competitive algorithm using passive techniques to localize faults in computer networks. the presented approach using end-to-end data detect that there are faults on the network, and then we use imperialist competitive algorithm (ica) to localize faults on the network. the aim of proposed approach is to minimize the cost of localization of faults in the network. according to simulation results, our algorithm is better than other state-of-the-art approaches that localize and repair all faults in a network.