Toward large-graph comparison measures to understand Internet topology dynamics
Lee Daryl, Hsu Ann
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By measuring network changes, we can get a better understanding of a network. Extending this to the Internet, we are able to understand the constantly occuring changes on an international scale. In this research, we propose a measure that conveys the relative magnitude of the change between two networks (i.e., Internet topology). The measure is normalised and intuitively gives an indication of whether the change is small or large. We start off by applying this measure to standard common graphs, as well as random graphs. These graphs were first simulated and the measurements taken; results were then proved theoretically. These corresponded to the simulation results, thus demonstrating correctness. For case studies, we compared actual implemented networks with that which is inferred by probes. This comparison was done to study how accurate the probes were in discovering actual network topology. Finally, we conducted real-world experiments by applying the measurements to certain segments of the Internet. We observed that the measurements indeed do pick up events which significantly influenced structural changes to the Internet.
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