A tractable analytical model for large-scale congested protein synthesis networks

Abstract

This paper presents an analytical model, based on finite capacity queueing network theory, to evaluate congestion in protein synthesis networks. These networks are modeled as a set of single server bufferless queues in a tandem topology. This model proposes a detailed state space formulation, which provides a fine description of congestion and contributes to a better understanding of how the protein synthesis rate is deteriorated. The model approximates the marginal stationary distributions of each queue. It consists of a system of linear and quadratic equations that can be decoupled. The numerical performance of this method is evaluated for networks with up to 100,000 queues, considering scenarios with various levels of congestion. It is a computationally efficient and scalable method that is suitable to evaluate congestion for large-scale networks. Additionally, this paper generalizes the concept of blocking: blocking events can be triggered by an arbitrary set of queues. This generalization allows for a variety of blocking phenomena to be modeled.