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Distributed computing applications are increasingly utilizing distributed data sources. However, the unpredictable cost of data access in large-scale computing infrastructures can lead to severe performance bottlenecks. Providing predictability in data access is thus essential to accommodate the large set of newly emerging large-scale, data-intensive computing applications. In this regard, accurate estimation of network performance is crucial to meeting the performance goals of such applications. Passive estimation based on past measurements is attractive for its relatively small overhead compared to relying on explicit probing. In this paper, the authors take a passive approach for network performance estimation. Their approach is different from existing passive techniques that rely either on past direct measurements of pairs of nodes or on topological similarities.
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