102 research outputs found
Heterogeneity in Distributed Live Streaming: Blessing or Curse?
Distributed live streaming has brought a lot of interest in the past few
years. In the homogeneous case (all nodes having the same capacity), many
algorithms have been proposed, which have been proven almost optimal or
optimal. On the other hand, the performance of heterogeneous systems is not
completely understood yet. In this paper, we investigate the impact of
heterogeneity on the achievable delay of chunk-based live streaming systems. We
propose several models for taking the atomicity of a chunk into account. For
all these models, when considering the transmission of a single chunk,
heterogeneity is indeed a ``blessing'', in the sense that the achievable delay
is always faster than an equivalent homogeneous system. But for a stream of
chunks, we show that it can be a ``curse'': there is systems where the
achievable delay can be arbitrary greater compared to equivalent homogeneous
systems. However, if the system is slightly bandwidth-overprovisioned, optimal
single chunk diffusion schemes can be adapted to a stream of chunks, leading to
near-optimal, faster than homogeneous systems, heterogeneous live streaming
systems
Converging an Overlay Network to a Gradient Topology
In this paper, we investigate the topology convergence problem for the
gossip-based Gradient overlay network. In an overlay network where each node
has a local utility value, a Gradient overlay network is characterized by the
properties that each node has a set of neighbors with the same utility value (a
similar view) and a set of neighbors containing higher utility values (gradient
neighbor set), such that paths of increasing utilities emerge in the network
topology. The Gradient overlay network is built using gossiping and a
preference function that samples from nodes using a uniform random peer
sampling service. We analyze it using tools from matrix analysis, and we prove
both the necessary and sufficient conditions for convergence to a complete
gradient structure, as well as estimating the convergence time and providing
bounds on worst-case convergence time. Finally, we show in simulations the
potential of the Gradient overlay, by building a more efficient live-streaming
peer-to-peer (P2P) system than one built using uniform random peer sampling.Comment: Submitted to 50th IEEE Conference on Decision and Control (CDC 2011
GLive: The Gradient overlay as a market maker for mesh-based P2P live streaming
Peer-to-Peer (P2P) live video streaming over the Internet is becoming increasingly popular, but it is still plagued
by problems of high playback latency and intermittent playback streams. This paper presents GLive, a distributed
market-based solution that builds a mesh overlay for P2P
live streaming. The mesh overlay is constructed such that (i) nodes with increasing upload bandwidth are located closer to the media source, and (ii) nodes with similar upload bandwidth become neighbours. We introduce a market-based approach that matches nodes willing and able to
share the stream with one another. However, market-based
approaches converge slowly on random overlay networks, and we improve the rate of convergence by adapting our market-based algorithm to exploit the clustering of nodes
with similar upload bandwidths in our mesh overlay. We address the problem of free-riding through nodes preferentially uploading more of the stream to the best uploaders. We compare GLive with our previous tree-based streaming protocol, Sepidar, and NewCoolstreaming in simulation, and our results show significantly improved playback continuity and playback latency
Variable Neighbor Selection in Live Peer-to-Peer Multimedia Streaming Networks
Data-driven (or swarming based) streaming is one of the popular ways to distribute live multimedia streaming traffic over Peer-to-Peer (P2P) networks. The efficiency and user satisfaction highly depend on the constructed overlays. The common neighbor selection algorithms in existing overlay construction schemes usually randomly select a fixed number of neighbors which satisfy the selection requirements, such as end-to-end delay or a peer\u27s sojourn time. However, this fixed random neighbor-selection algorithm (FRNS) neglects the peers\u27 upload bandwidth heterogeneity and therefore, the upload bandwidth cannot be efficiently used. In this paper, we propose a variable random neighbor-selection (VRNS) scheme to alleviate the problems due to bandwidth heterogeneity, and in which the number of neighbors with different upload bandwidths is dynamically determined by the statistical bandwidth information of the system. Our proposed scheme is shown to outperform FRNS based upon a large volume of carefully designed simulations
Stochastic Analysis of Self-Sustainability in Peer-Assisted VoDSystems
Abstract—We consider a peer-assisted Video-on-demand system, in which video distribution is supported both by peers caching the whole video and by peers concurrently downloading it. We propose a stochastic fluid framework that allows to characterize the additional bandwidth requested from the servers to satisfy all users watching a given video. We obtain analytical upper bounds to the server bandwidth needed in the case in which users download the video content sequentially. We also present a methodology to obtain exact solutions for special cases of peer upload bandwidth distribution. Our bounds permit to tightly characterize the performance of peer-assisted VoD systems as the number of users increases, for both sequential and nonsequential delivery schemes. In particular, we rigorously prove that the simple sequential scheme is asymptotically optimal both in the bandwidth surplus and in the bandwidth deficit mode, and that peer-assisted systems become totally self-sustaining in the surplus mode as the number of users grows large. I
Size Does Matter (in P2P Live Streaming)
Optimal dissemination schemes have previously been studied for peer-to-peer
live streaming applications. Live streaming being a delay-sensitive
application, fine tuning of dissemination parameters is crucial. In this
report, we investigate optimal sizing of chunks, the units of data exchange,
and probe sets, the number peers a given node probes before transmitting
chunks. Chunk size can have significant impact on diffusion rate (chunk miss
ratio), diffusion delay, and overhead. The size of the probe set can also
affect these metrics, primarily through the choices available for chunk
dissemination. We perform extensive simulations on the so-called random-peer,
latest-useful dissemination scheme. Our results show that size does matter,
with the optimal size being not too small in both cases
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