Reproduce “Taming the Heavy Tail: Age-Optimal Preemption” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Aimin Li, Yiğit İnce, Elif Uysal
TAILOR jointly chooses when to sample an update and when to preempt an unfinished one, balancing freshness against service progress and penalties. It uses state-dependent decisions for sampling and restart times. In simulations on the higher-variance of two equal-mean log-normal service models (mean 2), its average cost was 1.77 versus 53.5 for AoI-optimal non-preemptive sampling, a result for this modeled setting.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.