An Upload Bandwidth Threshold for Peer-to-Peer Video-on-Demand Scalability - Archive ouverte HAL Access content directly
Conference Papers Year : 2009

## An Upload Bandwidth Threshold for Peer-to-Peer Video-on-Demand Scalability

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Fabien Mathieu
Fabien de Montgolfier
Diego Perino
• Function : Author
Laurent Viennot

#### Abstract

We consider the fully distributed Video-on-Demand problem, where $n$ nodes called \emphboxes store a large set of videos and collaborate to serve simultaneously $n$ videos or less between them. It is said to be \emphscalable when $\Omega(n)$ videos can be distributively stored under the condition that any sequence of demands for these videos can always be satisfied. Our main result consists in establishing a threshold on the average upload bandwidth of a box, above which the system becomes scalable. We are thus interested in the normalized upload capacity $u=\frac{upload\ bandwidth}{video\ bitrate}$ of a box. The number $m$ of distinct videos stored in the system is called its catalog size. We show an upload capacity threshold of $1$ for scalability in a homogeneous system, where all boxes have the same upload capacity. More precisely, a system with $u<1$ has constant catalog size $m=O(1)$ (every box must store some data of every video). On the other hand, for $u>1$, an homogeneous system where all boxes have same upload capacity at least $u$ admits a static allocation of $m=\Omega(n)$ videos into the boxes such that any adversarial sequence of video demands can be satisfied. Moreover, such an allocation can be obtained randomly with high probability. This result is generalized to a system of boxes that have heterogeneous upload capacities under some balancing conditions.

### Dates and versions

inria-00471728 , version 1 (08-04-2010)

### Identifiers

• HAL Id : inria-00471728 , version 1
• DOI :

### Cite

Yacine Boufkhad, Fabien Mathieu, Fabien de Montgolfier, Diego Perino, Laurent Viennot. An Upload Bandwidth Threshold for Peer-to-Peer Video-on-Demand Scalability. 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2009, Rome, Italy. pp.1--10, ⟨10.1109/IPDPS.2009.5161047⟩. ⟨inria-00471728⟩

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