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Know when to persist: Deriving value from a stream...
Journal article

Know when to persist: Deriving value from a stream buffer

Abstract

We consider Persistence, a new online problem concerning optimizing weighted observations in a stream of data when the observer has limited buffer capacity. A stream of weighted items arrive one at a time at the entrance of a buffer with two holding locations. A processor (or observer) can process (observe) an item at the buffer location it chooses, deriving this way the weight of the observed item as profit. The main constraint is that the …

Authors

Georgiou K; Karakostas G; Kranakis E; Krizanc D

Journal

Theoretical Computer Science, Vol. 717, , pp. 47–61

Publisher

Elsevier

Publication Date

March 2018

DOI

10.1016/j.tcs.2017.05.021

ISSN

0304-3975