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- W2170068982 abstract "Internet distance prediction gives pair-wise latency information with limited measurements. Recent studies have revealed that the quality of existing prediction mechanisms from the application perspective is short of satisfactory. In this paper, we explore the root causes and remedies for this problem. Our experience with different landmark selection schemes shows that although selecting nearby landmarks can increase the prediction accuracy for short distances, it can cause the prediction accuracy for longer distances to degrade. Such uneven prediction quality significantly impacts application performance. Instead of trying to select the landmark nodes in some intelligent fashion, we propose a hierarchical prediction approach with straightforward landmark selection. Hierarchical prediction utilizes multiple coordinate sets at multiple distance scales, with the right scale being chosen for prediction each time. Experiments with Internet measurement datasets show that this hierarchical approach is extremely promising for increasing the accuracy of network distance prediction." @default.
- W2170068982 created "2016-06-24" @default.
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- W2170068982 date "2006-08-03" @default.
- W2170068982 modified "2023-09-24" @default.
- W2170068982 title "A Hierarchical Approach to Internet Distance Prediction" @default.
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- W2170068982 doi "https://doi.org/10.1109/icdcs.2006.7" @default.
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