The growing scale and importance of technological networks throughout the world has highlighted the devastating consequences of catastrophic network failures. In this paper, we address this crucial issue through a detailed analysis of network traffic distribution across network nodes, with the aim of developing an intelligent traffic control model. Specifically, we develop and demonstrate the Dynamically Adjusted Traffic Rates model, which aims to fairly distribute traffic amongst network nodes according to their network characteristics. Our model is independent of topology and is based on dynamically adjusted traffic rates and properties similar to those observed in real Internet traffic. In this paper our model is numerically analyzed over a variety of network topologies to display its chaotic features leading to self-similarity. The model is inspired by biological evidence.
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