hal-00683827, version 1
CCN Interest Forwarding Strategy as Multi-Armed Bandit Model with Delays
N° RR-7917 (2012)
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.
- a – BCAM -- Basque Center for Applied Mathematics
- 1:
- INRIA – Université Montpellier II - Sciences et techniques
- 2:
- Basque Center for Applied Mathematics
- Domain : Computer Science/Networking and Telecommunication
- Keywords : Information Centric Networks – Content Centric Networks – Interest Forwarding – Multi-Armed Model with Delays
- Internal note : RR-7917
- Available versions : v1 (2012-03-31) v2 (2012-04-02)
- hal-00683827, version 1
- http://hal.inria.fr/hal-00683827
- oai:hal.inria.fr:hal-00683827
- From:
- Submitted on: Thursday, 29 March 2012 23:21:54
- Updated on: Saturday, 31 March 2012 08:00:40






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