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Unsupervised ML for 5G Low Latency by Neel is a document available to read on EtoBox.

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This 3-sentence summary provides the essential information about the document: The document is an abstract for a paper presented at the IEEE International Performance Computing and Communications Conference in December 2017 in San Diego, CA. The paper proposes an unsupervised machine learning algorithm to determine the locations of fog nodes in 5G heterogeneous networks in order to reduce latency through soft clustering, where low power nodes can probabilistically connect to multiple fog nodes. Simulation

Author

Neel

Language

EN