Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Modern control theory (3rd ed.)
Modern control theory (3rd ed.)
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In network simulations, complex dynamical behavior is Previous analysis has identified limitations associated with Markov Chain Models and has established a need for the analysis of network dynamics through bound-queue/minimum-interarrival-time simulation models. In network simulations, complex dynamical behavior is observed even for simplistic stationary offered loads. An important contributor to the complexity of the network dynamics is the routing system. When a network consists of a large number of nodes, a routing system is applied in order to route traffic in an efficient manner between the nodes. The routing system has an important effect on the resulting network dynamics. This paper will discuss the complex dynamical behavior observed in networks controlled by distributed adaptive routing systems. This methodology can be applied during stability analyses of routing systems and is useful in system-level simulation verification.