Optimal redundancy allocation to maximize multi-state computer network reliability subject to correlated failures

Modern society depends on the stability of computer networks. One way to achieve this goal is to determine the optimal redundancy allocation such that system reliability is maximized. Redundancy requires that each edge in computer networks possess several binary-state physical lines allocated in parallel. A computer network implementing redundancy allocation is called a multi-state computer network (MSCN), since each edge can exhibit multiple states with a probability distribution according to the number of binary-state physical lines that are operational. However, past research often fails to consider the possibility of correlated failures. This study applies a correlated binomial distribution to characterize the state distribution of each edge within a network and a redundancy optimization approach integrating simulated annealing (SA), minimal paths, and correlated binomial distribution is proposed. The approach is applied to four practical computer networks to demonstrate the computational efficiency of the proposed SA relative to several popular soft computing algorithms.