arXiv Open Access 2018

Feedforward Neural Networks for Caching: Enough or Too Much?

Vladyslav Fedchenko Giovanni Neglia Bruno Ribeiro

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Abstrak

We propose a caching policy that uses a feedforward neural network (FNN) to predict content popularity. Our scheme outperforms popular eviction policies like LRU or ARC, but also a new policy relying on the more complex recurrent neural networks. At the same time, replacing the FNN predictor with a naive linear estimator does not degrade caching performance significantly, questioning then the role of neural networks for these applications.

Topik & Kata Kunci

cs.NI

Penulis (3)

Vladyslav Fedchenko

Giovanni Neglia

Bruno Ribeiro

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APA MLA BibTeX

Fedchenko, V., Neglia, G., Ribeiro, B. (2018). Feedforward Neural Networks for Caching: Enough or Too Much?. https://arxiv.org/abs/1810.06930

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓