Abstract: Channel access delays and reception uncertainty are modeled as protocol-independent generic processes that are optimized for improved simulation performance. The generic process components are designed such that each different protocol can be modeled using an arrangement of these components that is specific to the protocol. In this way, speed and/or accuracy improvements to the generic process components are reflected in each of such protocol models. If an accurate analytic model is not available for the generic process component, a prediction engine, such as a neural network, is preferably used. The prediction engine is trained using the existing detailed models of network devices. Once trained, the prediction engine is used to model the generic process, and the protocol model that includes the generic component is used in lieu of the detailed models, thereby saving substantial processing time.

Abstract: Traffic flows through an administered network from an off-network source and/or to an off-network destination are simulated and analyzed by selecting an ingress and/or egress node within the administered network, the ingress node capable of collecting traffic from an off-network source, and the egress node capable of routing traffic to an off-network destination. Traffic flow is mapped from the source or ingress node through the administered network to the egress node. The traffic flow may be simulated and analyzed. The ingress and/or egress nodes may be selected in a variety of ways.

Abstract: Channel access delays and reception uncertainty are modeled as protocol-independent generic processes that are optimized for improved simulation performance. The generic process components are designed such that each different protocol can be modeled using an arrangement of these components that is specific to the protocol. In this way, speed and/or accuracy improvements to the generic process components are reflected in each of such protocol models. If an accurate analytic model is not available for the generic process component, a prediction engine, such as a neural network, is preferably used. The prediction engine is trained using the existing detailed models of network devices. Once trained, the prediction engine is used to model the generic process, and the protocol model that includes the generic component is used in lieu of the detailed models, thereby saving substantial processing time.

Abstract: Traffic flows through an administered network from an off-network source and/or to an off-network destination are simulated and analyzed by selecting an ingress and/or egress node within the administered network, the ingress node capable of collecting traffic from an off-network source, and the egress node capable of routing traffic to an off-network destination. Traffic flow is mapped from the source or ingress node through the administered network to the egress node. The traffic flow may be simulated and analyzed. The ingress and/or egress nodes may be selected in a variety of ways.