Keep-Alive Caching for the Hawkes Process

Abstract

We study the design of caching policies in applications such as serverless computing where there is not a fixed size cache to be filled, but rather there is a cost associated with the time an item stays in the cache. We present a model for such caching policies which captures the trade-off between this cost and the cost of cache misses. We characterize optimal caching policies in general and apply this characterization by deriving a closed form for Hawkes processes. Since optimal policies for Hawkes processes depend on the history of arrivals, we also develop history-independent policies which achieve near-optimal average performance. We evaluate the performances of the optimal policy and approximate polices using simulations and a data trace of Azure Functions, Microsoft’s FaaS (Function as a Service) platform for serverless computing

Cite

Text

Narayana and Kash. "Keep-Alive Caching for the Hawkes Process." Uncertainty in Artificial Intelligence, 2023.

Markdown

[Narayana and Kash. "Keep-Alive Caching for the Hawkes Process." Uncertainty in Artificial Intelligence, 2023.](https://mlanthology.org/uai/2023/narayana2023uai-keepalive/)

BibTeX

@inproceedings{narayana2023uai-keepalive,
  title     = {{Keep-Alive Caching for the Hawkes Process}},
  author    = {Narayana, Sushirdeep and Kash, Ian A.},
  booktitle = {Uncertainty in Artificial Intelligence},
  year      = {2023},
  pages     = {1499-1509},
  volume    = {216},
  url       = {https://mlanthology.org/uai/2023/narayana2023uai-keepalive/}
}