Fast Near-Optimal Algorithm for Delivering Multiple Live Video Channels in CDNs

Liu, Jiayi; Simon, Gwendal

doi:10.1109/icccn.2013.6614138

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…The first set of work related to discretized streaming has been published in a conference paper [23]. This paper significantly extend our previous work by considering a more general application scenario and proposing fast near-optimum algorithm for it.…”

Section: Introductionmentioning

confidence: 87%

Optimal tree packing for discretized live rate-adaptive streaming in CDN

2015

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Section: Introductionmentioning

confidence: 87%

Optimal tree packing for discretized live rate-adaptive streaming in CDN

2015

Self Cite

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“…These works cannot be extended to multi-source multi-channel live streaming due to the shared resources such as link capacity and server upload bandwidth. Though some works have been done on multi-channel P2P live streaming [8]- [12], they consider different objective functions, such as maximizing bandwidth to support more users or minimizing the load of servers through collaboration of users. Few have addressed how to optimize the overall streaming delay, which is an important metric for user experience in live streaming.…”

Section: Introductionmentioning

confidence: 99%

Delay optimization for Multi-source Multi-channel Overlay live Streaming

Dai

Chang

Chan

2015

2015 IEEE International Conference on Communications (ICC)

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Abstract-In order to provide scalable live streaming service, a content provider often deploys an overlay cloud consisting of distributed servers which collaboratively exchange streams with each other. We consider an overlay consisting of multiple live channels originating from multiple sources. Server bandwidth and end-to-end network bandwidth are shared among these channels. The stream of each channel is divided into multiple substreams of a certain bitrate, each of which is pushed via a tree to the servers that subscribe to the channel. The critical and challenging issue is then how to optimize the topology of the substream trees so as to minimize the maximum channel delay (defined as the delay from the source to the subscribing servers).There has been little work on the optimization of such multisource multi-channel live streaming network. We first formulate the problem which comprehensively and realistically captures various delay and bandwidth components, and show that it is NP-hard. We then propose an efficient algorithm called COMMOS (Collaborative Multi-source Multi-channel Streaming Overlay) which achieves low channel delay. Extensive simulation results based on real Internet topologies show that COMMOS outperforms other state-of-the-art schemes by a wide margin (often by more than 40%), due to its better utilization of network resources.

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“…Recent works have shown that coupling layered video with adaptive streaming [34] can generate important bandwidth savings but such solution is still in its infancy today. Finally, a discretized streaming model for live rate-adaptive video streaming has been proposed in [35]. The goal is to maximize the utility of delivered streams.…”

Section: ) Overall Performancesmentioning

confidence: 99%

Optimal Delivery of Rate-Adaptive Streams in Underprovisioned Networks

Liu

Rosenberg

Simon

et al. 2014

IEEE J. Select. Areas Commun.

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Abstract-The growth of Internet video traffic imposes a severe capacity problem in today's Content Delivery Network (CDN). Rate-adaptive streaming technologies, such as the Dynamic Adaptive Streaming over HTTP (DASH) standard, reinforces this problem in the core CDN infrastructure since delivering one video means delivering multiple representations for an aggregated bit-rate that is commonly over 10 Mbps. In this paper, we explore better trade-offs between CDN infrastructure cost and Quality of Experience (QoE) of the end-users for live broadcast video streaming applications. We consider in particular underprovisioned CDN networks, our goal being to maximize the QoE for the population of heterogeneous end-users despite the lack of resources in the intermediate CDN equipments. We show that previous theoretical models based on elastic bit-rates do not fit for this context. We propose a user-centric discretized streaming model where the satisfaction of end-users is related to the context and where a stream has to be either delivered in its entirety, or not delivered at all. We first formulate an Integer Linear Program (ILP) that achieves the optimal delivery through a multi-tree delivery overlay. The evaluation of the ILP shows the benefits of this model. We then design a practical system by revisiting the three main algorithms implemented in CDN: userto-server assignment, content placement and content delivery. At last, we use a realistic trace-driven large-scale simulator to study the performances of our system. In particular, we show that the population of users is reasonably well served (three quarters of the population do not experience degradation) even when the CDN infrastructure experiences a severe underprovisioning (less than half of the required infrastructure).

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Fast Near-Optimal Algorithm for Delivering Multiple Live Video Channels in CDNs

Cited by 4 publications

References 17 publications

Optimal tree packing for discretized live rate-adaptive streaming in CDN

Optimal tree packing for discretized live rate-adaptive streaming in CDN

Delay optimization for Multi-source Multi-channel Overlay live Streaming

Optimal Delivery of Rate-Adaptive Streams in Underprovisioned Networks

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