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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

Lecture Notes in Computer Science, Vol. 9778, , pp. 101–112

Publisher

Springer Nature

Publication Date

2016

DOI

10.1007/978-3-319-41168-2_9

ISSN

0302-9743

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