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Liquidstream II—Scalable P2P overlay optimization with adaptive minimal server assistance for stable and efficient video on demand

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Abstract

In recent years, a number of research efforts have focused on effective and stable P2P architectures aiming at large scale and low bandwidth cost, real time video streaming systems. Particularly, live streaming and Video-on-Demand (VoD) systems have lately attracted much interest. While many efforts mainly focused on the development of distributed schedulers for content exchange among the participating peers, there are still open fundamental questions regarding the graph (P2P overlay) structure that determines the set of peers with which each peer communicates. Additionally, the way that cloud media servers support these systems is still an open issue. In this paper, we consider a BitTorrent-like VoD system and focus on the following questions: (1) how a distributed-scalable architecture can be formed in a highly heterogeneous and dynamic environment such that it dynamically manages the P2P overlay by means of exploiting the available upload bandwidth of the participating peers, and (2) how a cloud media (bandwidth provider) server reduces the amount of the bandwidth percentage contributed to the system in order to support a larger number of peers. To illustrate the success of our approach, we have developed an extensive P2P VoD simulator for demonstrating the efficiency, scalability and stability of our work under variant and dynamic conditions. Our system guarantees the uninterrupted and efficient video distribution, even in extreme cases of peer arrivals and departures at high rates.

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Acknowledgments

This work was partially funded from STEER (Social Telemedia Environment for Experimental Research) which is an EU project funded under the call FP7-ICT-2011-8 and our University coordinates.

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Correspondence to Konstantinos Deltouzos.

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Deltouzos, K., Gkortsilas, I., Efthymiopoulos, N. et al. Liquidstream II—Scalable P2P overlay optimization with adaptive minimal server assistance for stable and efficient video on demand. Peer-to-Peer Netw. Appl. 8, 260–275 (2015). https://doi.org/10.1007/s12083-013-0230-6

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  • DOI: https://doi.org/10.1007/s12083-013-0230-6

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