Efficient Network Reliability Evaluation for Client-Server Model

Network reliability, i.e., the probability of connecting a set of specified nodes under stochastic link failure, is a key indicator of network infrastructure, such as communication and power. Since network reliability evaluation is a computationally heavy task, several methods have been proposed to efficiently perform it. However, modern network infrastructures follow the client-server model, where many clients are served independently, so we have to evaluate the network reliability for every set consisting of the servers and each client. This evaluation process involves repetitive evaluations while changing the set, which imposes a heavy burden on network operators. This paper proposes a method that efficiently performs network reliability evaluation for the client-server model. Since our method is designed to evaluate reliability for multiple clients without explicit repetition, the computational complexity does not increase compared to the case where existing methods evaluate reliability for a single client. Numerical experiments using datasets of various topologies, including real communication networks, reveal great efficiency. Our method is more than 100 times faster than an existing method that requires repeated evaluation, e.g., it takes only 27 seconds to compute the reliability for 670 clients on a large network with 821 links.