Maximization Of Network Reliability Using Ann Under Node-Link Failure Model

摘要

The network Reliability optimization problem for any type of interconnection network is to maximize the network reliability subjected some constraint such as the total cost of the network. Even though, the problem is NP-Hard, many researchers have solved this problem in different ways but with a common assumption that nodes are perfect. But, this assumption is quite unrealistic in nature. In this paper, a new method based on artificial network is proposed to solve the network reliability optimization problem considering both the nodes and links of the interconnection network to be imperfect. The problem is mapped onto an optimization Artificial Neural Network by constructing an energy function whose minimization process drives the neural network into one of its stable states. This stable state corresponds to a solution for the network reliability problem. Some standard methods are studied and modified approximately so that they would work considering the node failure. The results of these methods are compared against the result of the proposed method. The comparison strongly supports that the proposed method provides a better maximization of network reliability than its counterparts under same working environment.