Illuminating the hidden challenges of data-driven CDNs

EuroMLSys '23: Proceedings of the 3rd Workshop on Machine Learning and Systems(2023)

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摘要
While Data-driven CDNs have the potential to provide unparalleled performance and availability improvements, they open up an intricate and exciting tapestry of previously un-addressed problems. This paper highlights these problems, explores existing solutions, and identifies open research questions for each direction. We, also, present a strawman approach, Guard-Rails, that embodies preliminary techniques that can be used to help safeguard data-driven CDNs against the identified perils.
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