Integral Caching using Online Mirror Descent in a Networked Context

Bachelor thesis (2022)

Authors

Q.J. Oschatz Electrical Engineering, Mathematics and Computer Science

Contributors

G. Iosifidis Embedded Systems - EEMCS (mentor)
N. Mhaisen Embedded Systems - EEMCS (mentor)
T. Si Salem Embedded Systems - EEMCS (mentor)
A. Hanjalic Intelligent Systems (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Quentin Oschatz
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Published Date

24-06-2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This paper explores algorithms to optimize networked caching, where requests for files can be handled by a local cache instead of a remote server. Caches work collaboratively to prevent redundant caching, and each new batch of file requests is used to update the entire network. Data is cached in an integral manner, meaning that only discrete files or chunks can be stored, not fractions of them. Bipartite networks are studied, though the proposed model supports arbitrary network topologies. The approach is based upon an Online Mirror Descent (OMD) policy, which has been shown to have sublinear regret in single cache scenarios.