A Novel Sum-of-Disjoint-Products Technique for Reliability Evaluation of Multistate Consumer Electronics Communication Flow Network

IoT-enabled consumer electronics (CE) communication networks, which involve billions of connected consumer devices, can be aptly modeled as Multistate Flow Networks (MFN). In such networks, the edges (transmission links) and nodes (CE devices/ access points) are characterized by multi-valued capacity states. Evaluating the reliability of these intricate networks presents an NP-hard computational challenge as the network grows. In this study, we propose a novel algorithm founded on the Sum of Disjoint Products (SDP) concept to compute the probability of successfully transmitting d units of data from a source node to a destination node of the MFN. To validate the correctness and robustness of our approach, we illustrate the algorithm’s application using a benchmark network sourced from relevant literature. Additionally, we demonstrate the applicability and scalability of the proposed work through computational experiments, comparing it with two best-known existing MFN reliability evaluation methods. Our method surpasses both the methods by achieving a remarkable 84% and 70% reduction in the computations required to evaluate reliability.