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In this article, we propose a novel analytical model based on queuing network to evaluate virtualized multi-tier applications.
This paper proposes an approximation model based on queuing network theory to analyze the impact of order batching and picking area zoning on the mean order throughput time in a pick-and-pass order picking system.
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The proposed modeling approach is based on queuing networks and discrete-event systems, where connection of elementary queues representing building elements allows to simulate complex environments.
Formal performance prediction methods, based on queueing network models, allow evaluating software architectural designs for performance.
The performance models are based on queueing-network models abstracted from the system and enhanced by machine learning algorithms to correlate system workload attributes with performance attributes.
In this paper, we develop a modeling method, based on queuing theory, for the solution of network performance problems faced when trying to support real-time services over Internet Protocol (IP) network.
Simulation results are generated to evaluate the performance of the proposed method in terms of supporting the QoS and improving the network scalability based on queuing delay control and adjustment.
Then we present a programming formulation for circulation network design with blocking probability control based on the queuing network model.
Arena is a simulation package based on queuing theory.
Another way to analyze the architecture is to model it based on queuing theory.
Exponentially distributed duty cycle models were presented based on queuing theory in [58,59].
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