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The platform is designed to exploit the synergy of two classes of network connections dedicated and opportunistic.
Its basic purpose is to separate different classes of network traffic, which are then transported over disjoint logical topologies.
Finally, a new empirical evaluation methodology for classifying irregular topologies and relating network behavior to various classes of network topologies is introduced.
Classes of network games such as First Person Shooters (FPS) and Real-Time Strategy (RTS) differ in their user interaction model and hence susceptibility to latency.
We show that these paradoxes are specific examples of more general classes of network change properties that we term the "least congestible route" and "size" principles, respectively.
The simultaneous use of many classes of network behaviors allows for the unsupervised learning/categorization of perceptual patterns (through input compression) and the concurrent encoding of proximities in a multidimensional space.
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We interpret these findings in the context of some well understood prototypical classes of networks.
These classes of networks include multi-square, convex-bipartite, and convex-split networks.
Thus, the designs of multiple ISTs on several classes of networks have been widely investigated.
Thus, the designs of independent spanning trees in several classes of networks have been widely investigated.
When efficiency and robustness requirements are both important to varying degrees, other classes of networks such as the "hub" emerge.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com