Designing overlay multicast networks for streaming

Abstract

In this paper we present a polynomial time approximation algorithm for designing a multicast overlay network. The algorithm finds a solution that satisfies capacity and reliability constraints to within a constant factor of optimal, and cost to within a logarithmic factor. The class of networks that our algorithm applies to includes the one used by Akamai Technologies to deliver live media streams over the Internet. In particular, we analyze networks consisting of three stages of nodes. The nodes in the first stage are the sources where live streams originate. A source forwards each of its streams to one or more nodes in the second stage, which are called reflectors. A reflector can split an incoming stream into multiple identical outgoing streams, which are then sent on to nodes in the third and final stage, which are called the sinks.As the packets in a stream travel from one stage to the next, some of them may be lost. The job of a sink is to combine the packets from multiple instances of the same stream (by reordering packets and discarding duplicates) to form a single instance of the stream with minimal loss. We assume that the loss rate between any pair of nodes in the network is known, and that losses between different pairs are independent, but discuss extensions in which some losses may be correlated.

An efficient streaming method in overlay multicast networks

“…Chin's [13] work aims at reliable delivery of video data via biased protection of essential signals whereas Andreev's et al [14] work offers reliability through sending multiple redundant video streams which undermines the key objective of multicast technology, saving bandwidth. In order to facilitate biased protection towards base layer information, it is necessary to interleave base data with enhancement data.…”

“…The method proposed herein aims at improving Andreev's et al work [14]. Their overlay multicast network is designed to transmit video signals from the encoder to the users with an attempt to ease bottlenecks in the server and the network.…”

“…( (4,4), E x (14,1), E x (24,2), E x (9,1)}, B x (2), {E x (22,1), E x (8,1), E x (18,1), E x (14,2)}, ….…”

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

“…Although for live streaming, the delivery process actually starts from CDN sources and involves the organization of the delivery infrastructure. The earliest works (mainly [3,5] and references in [24]) did not deal with multiple streams, which is the main challenge in our work. The most recent works [1,4,26] consider the lack of resources and multiple streams, however, their objective is to reduce the bandwidth cost subject to the resource constraints.…”

“…A recent survey [27] has referenced 438 significant papers related to content delivery through peer-to-peer (P2P), peer-assisted networking and CDNs; however, only two citations referenced live streaming in CDNs [3,5]. Most recent works related to live streaming in CDNs [1,4,26] target to reduce the transmission cost.…”