TRANSIT: Supporting transitions in Peer-to-Peer live video streaming

Abstract

Abstract-The transmission of video content accounts for a large share of today's Internet traffic. While Video-on-Demand (VoD) substantially contributes to this, live streaming events such as video broadcasts from the Olympic Games can cause very high traffic volumes in the short term as well. Such peaks along with high fluctuations triggered by sudden changes in the behavior of users make the design of live streaming systems particularly challenging. Peer-to-Peer (P2P) has proven to be a scalable approach for disseminating content to a large number of users. Accordingly, the body of research offers numerous P2P live streaming approaches tailored towards specific scenarios and assumptions. However, no single approach is able to perform well under all possible conditions. Keeping up a high performance when conditions are changing is a challenge, since topology management and scheduling mechanisms cannot be exchanged easily. Therefore, this paper proposes TRANSIT, a new approach going beyond existing works in that it supports transitions between different live streaming mechanisms. TRANSIT makes different configurations of such mechanisms seamlessly exchangeable to enable the optimal choice of configurations for a wide range of live streaming scenarios. The approach is evaluated using measurement-and trace-based workloads. The results show that TRANSIT is able to maintain a high performance at a low overhead in highly fluctuating environments, whereas static configurations show serious performance degradations.

How to adapt: SVC-based quality adaptation for hybrid peercasting systems

“…Hybrid P2P live streaming systems often employ an architecture using two delivery mechanisms in combination: a tree/push based delivery mechanism is used for stable peers, while pieces of data (chunks) not delivered via the tree are requested using a pull based mesh [18], [16]. As modern video codecs allow scaling the video quality along multiple dimensions (e.g., resolution, frame rate, and frame compression [13]), an effective scheduling algorithm does not only have to deal with push and pull based scheduling, but also has to decide simultaneously, which video quality along which dimension is to be delivered using which mechanism.…”

Transitions in Live Video Streaming Services

“…Therefore, a tracking functionality is hosted on the central server to provide node contacts used for the initial neighborhoods in the P2P topology, while the exchange of media chunks is then done completely decentralized. As [3] has shown in live streaming scenarios: a tree topology is beneficial to reduce delay between streaming nodes due to the push-based delivery of chunks. Thus, the system aims to arrange clients in a tree, but allows an hybrid video chunk exchange in cases of high churn or if chunks are dropped due to unreliable UDP transmissions.…”

“…Streaming should be continued in a consistent quality for all users even though the operations on the network change. The used P2P system is based on Wichtlhuber et al's TRANSIT [3]. The C/S system follows a classical star topology, where joining nodes contact a server and are provided with small video segments, so called chunks by only this central source.…”

2017 Proceedings of the Ninteenth Workshop on Algorithm Engineering and Experiments (ALENEX)

“…Achieving crucial distance reductions in the first round, LoMbA even outperforms the specialized tree adaptation algorithm [7] for both types of graphs (random trees of size 10000 and Transit [34] trees with 600 nodes). In the subsequent rounds, LoMbA still achieves slight improvements.…”

“…Moreover, we varied θ for our algorithm to generate additional target motif signatures. We used PeerfactSim.KOM [28] to run the video streaming system Transit [34] and exported video streaming trees with 600 nodes. To conduct an evaluation of LoMbA for even larger graphs, we additionally used random rooted trees with 10000 nodes as input topologies.…”