Efficient allocation of seed servers in peer-to-peer streaming systems with scalable videos

We study streaming of scalable videos over peer-to-peer (P2P) networks. We focus on efficient management of seed servers resources, which need to be deployed in the network to make up for the limited upload capacity of peers in order to deliver higher quality video streams. These servers have finite serving capacity and are often loaded with a volume of requests larger than their capacity. We formulate the problem of allocating this capacity for optimally serving scalable videos. We show that this problem is NP-complete, and propose two approximation algorithms to solve it. The first one allocates seeding resources for serving peers based on dynamic programming, and is more suitable for small seeding capacities (les 10 Mbps). The second algorithm follows a greedy approach and is more efficient for larger capacities. We evaluate the proposed algorithms analytically and in a simulated P2P streaming system. The results confirm the efficiency and near-optimality of the proposed algorithms, and show that higher-quality videos are delivered to peers if our algorithms are employed for allocating seed servers.