# CCN Interest Forwarding Strategy as Multi-Armed Bandit Model with Delays

1 MAESTRO - Models for the performance analysis and the control of networks
CRISAM - Inria Sophia Antipolis - Méditerranée
2 Networks
BCAM - Basque Center for Applied Mathematics
Abstract : We consider Content Centric Network (CCN) interest forwarding problem as a Multi-Armed Bandit (MAB) problem with delays. We investigate the transient behaviour of the $\eps$-greedy, tuned $\eps$-greedy and Upper Confidence Bound (UCB) interest forwarding policies. Surprisingly, for all the three policies very short initial exploratory phase is needed. We demonstrate that the tuned $\eps$-greedy algorithm is nearly as good as the UCB algorithm, the best currently available algorithm. We prove the uniform logarithmic bound for the tuned $\eps$-greedy algorithm. In addition to its immediate application to CCN interest forwarding, the new theoretical results for MAB problem with delays represent significant theoretical advances in machine learning discipline.
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Type de document :
Rapport
[Research Report] RR-7917, INRIA. 2012

https://hal.inria.fr/hal-00683827
Contributeur : Konstantin Avrachenkov <>
Soumis le : dimanche 1 avril 2012 - 23:08:42
Dernière modification le : samedi 27 janvier 2018 - 01:31:43
Document(s) archivé(s) le : lundi 2 juillet 2012 - 03:23:36

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RR-7917.pdf
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• HAL Id : hal-00683827, version 2
• ARXIV : 1204.0416

### Citation

Konstantin Avrachenkov, Peter Jacko. CCN Interest Forwarding Strategy as Multi-Armed Bandit Model with Delays. [Research Report] RR-7917, INRIA. 2012. 〈hal-00683827v2〉

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