Content Delivery Networks J. Famaey
Interconnection Working Group S. Latre
Internet-Draft UGent - IBBT
Intended status: Informational September 27, 2012
Expires: March 31, 2013
Experiments on HTTP Adaptive Streaming over interconnected Content
Delivery Networks
draft-famaey-cdni-has-experiments-00
Abstract
This document reports experimental results on the delivery of HTTP
Adaptive Streaming (HAS) content over interconnected Content Delivery
Networks (CDNs). Specifically, the implications of CDN request
routing between CDNs and HTTP redirection on the quality of delivered
HAS content are investigated.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Experimental Setup . . . . . . . . . . . . . . . . . . . . . . 3
3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 8
5. Security Considerations . . . . . . . . . . . . . . . . . . . . 9
6. References . . . . . . . . . . . . . . . . . . . . . . . . . . 9
6.1. Normative References . . . . . . . . . . . . . . . . . . . 9
6.2. Informative References . . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 9
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1. Introduction
HTTP Adaptive Streaming (HAS) refers to a set of novel streaming
approaches, which deliver streaming media content over the HTTP
protocol. The content is split into chunks, offered in several
quality layers. This allows the client to dynamically adapt the
requested quality, based on available network resources and device
capabilities. Delivering HAS content across multiple interconnected
CDNs introduces some new opportunities and challenges. Specifically,
it becomes possible to distribute the chunks of a single HAS content
stream across multiple CDNs, based on chunk popularity, Quality of
Service requirements, resource availability, economic or other
factors.
Every HAS content stream is accompanied by a Manifest File, which
lists the chunks of each quality layer and specifies their location
in the form of a URL. As stated in [I-D.brandenburg-cdni-has],
several alternative methods exist for specifying chunk locations:
o Relative URLs: The URLs specified in the Manifest File are
relative to the Manifest File's location and thus all located on
the same surrogate.
o Absolute URLs with Redirection: The Manifest File specifies the
fully qualified URL of each chunk. These URLs, however, direct
the client towards the CDN's request routing node, which in turn
uses HTTP redirection to send the client to the surrogate hosting
the actual chunk.
o Absolute URLs without Redirection: The URL points directly to the
surrogate hosting the chunk, effectively allowing the client to
circumvent the CDN request routing process.
This document aims to evaluate and compare different request routing
policies for HAS content, derived from these addressing mechanisms,
that can be used in CDN-interconnection scenarios.
2. Experimental Setup
The scenario used as a basis for the experiments consists of two
interconnected CDNs. The downstream CDN is located close to the end-
user (e.g., a telco CDN), while the upstream CDN is positioned
further (e.g., in the core Internet). The upstream CDN is assumed to
be the main storage facility of the original content. As such, it
hosts the Manifest file but can offload content chunks to one or more
downstream CDNs. Figure 1 graphically depicts the scenario and lists
the parameters that were varied in the course of the experiments.
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The upstream CDN request router, upstream CDN content server,
downstream CDN request router and downstream CDN content server are
depicted as uRR, uCS, dRR and dCS, respectively. During the
experiments, three parameters were varied: the one-way Internet delay
D, the per-client bandwidth B and the HAS client buffer size P. The
bandwidth on all other network links was set to 100 Mbps, while the
one-way network delay was set to 5 ms. The round trip time (RTT)
between two nodes can be calculated as the sum of the one-way delays
of the links on the path between them, multiplied by two. In the
performed experiments, the RTT between the client and the dRR/dCS is
40 ms, as the path connecting them consists of 4 links. The RTT
between the client and the uRR/uCS equals (60+2D) ms, as the path
between them contains 6 links and the Internet path. Note that the
figure presents a high level, simplified view of the network topology
and does not show all individual network links and routers. The
processing delay on the CDN surrogates is not taken into account, as
it is assumed to be negligible compared to the network delay.
|B Mbps
+---+ +---+ +---+ +---+ |bandwidth
|uRR| |uCS| D ms delay |dRR| |dCS| |
+---+ +---+ <-------------> +---+ +---+ | |P second
| | | | | |buffer
,--,--,--. ,--,--. ,--,--,--. | v
,-' `-. ,-' `-. ,-' `-. v +------+
( Upstream CDN )===( Internet )===( Downstream CDN )===|Client|
`-. ,-' `-. ,-' `-. ,-' +------+
`--'--'--' `--'--' `--'--'--'
Figure 1: Evaluation scenario and parameters
Three alternative request routing policies are evaluated and
compared:
o UpstreamRR: The Manifest File points to the uRR for every chunk.
If the chunk is located within the upstream CDN's network, the uRR
sends the client a HTTP redirect request to point it to the
correct uCS. Otherwise, the uRR redirects the client to dRR,
which in turn redirects it to the correct dCS.
o DirectRR: The Manifest File immediately points to the correct
request router, which redirects the client to the correct content
server. This policy thus allows the client to circumvent going
via the upstream CDN's network if the chunk is located downstream.
o DirectCS: The Manifest File immediately points to the correct
content server, which allows the client to download segments
without being redirected. Compared to the DirectRR policy, the
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indirection of contacting the dRR is avoided.
The UpstreamRR policy can be seen as the traditional CDN-I approach,
where clients always contact the original CDN and HTTP redirection is
used to point them to interconnected CDNs when necessary. It does
not require any Manifest File rewriting. Additionally, the upstream
CDN does not need any detailed information about chunk locations, as
it only needs to redirect clients to the downstream request router.
The DirectRR and DirectCS policies are more complex, as they require
the upstream CDN to rewrite the original Manifest File.
Additionally, when using the DirectCS policy, the downstream CDN
either needs to share detailed chunk location information with the
upstream CDN or the interconnected CDNs need to collaborate in
creating the Manifest File.
The presented policies differ mostly in addressing chunks located in
the downstream CDN. As such, the experiments evaluate a scenario
where a single client downloads 100 HAS video chunks (of 2 seconds
each) from a content server located within the downstream CDN. The
constant bitrate video is available in 3 qualities, with bitrates 500
kbps, 1 Mbps and 2 Mbps.
As the end-user Quality of Experience (QoE) depends on several
factors, multiple evaluation metrics are used in the comparison:
o Average played quality: The played quality layer, averaged over
all chunks and specified in terms of bitrate. This is expressed
in megabits per second (Mbps), representing the bandwidth required
for downloading the played quality layers.
o Total buffer starvation time: The accumulated time during which
the client needs to rebuffer the chunks (excluding the original
start-up). A rebuffering occurs when a chunk is not available at
the client, while it is already required for decoding. This leads
to frame freezes, as the client needs to wait for the next chunk
to arrive, which significantly reduces QoE.
o Start-up delay: The time between the initial HTTP request for the
first chunk, performed by the client, and the time when the chunk
actually starts playing.
All reported results were obtained using the NS-3 simulation
environment [ns3] in combination with the Network Simulation Cradle
(NSC) [nsc]. NS-3 is a discrete-event network simulator for Internet
systems. NSC allows NS-3 to interface directly with the kernel's TCP
implementation, generating more accurate and realistic results. The
used HAS client rate adaptation algorithm is based on the first
version of the client algorithm incorporated in Microsoft's
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SmoothStreaming client. The source code of this algorithm can be
retrieved from CodePlex [msscode].
3. Results
This section lists and discusses experimental results on the average
played video quality and the start-up delay. Results on buffer
starvation are omitted, as they did not occur in the depicted
scenarios.
Figure 2 depicts the average played quality (in Mbps) as a function
of the client bandwidth B, client buffer size P and one-way Internet
delay D. The depicted results show that, as expected, the delivered
quality for the DirectRR and DirectCS policies is independent of the
network delay D between the Interconnected CDNs. On the other hand,
when using the standard UpstreamRR policy, quality of the delivered
HAS content degenerates significantly as the delay increases. The
exact breakpoint at which quality starts degrading does depend on
other factors, of which the available bandwidth is the most
important. Specifically, at a bandwidth of 5 Mbps, significant
quality reductions are visible for upstream CDN network delays of
more than 100 ms, while this breakpoint increases to over 200 ms for
a bandwidth of 100 Mbps.
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+----------+---------+----------+--------------------------------------+
| | | | Average played quality (Mbps) |
| B (Mbps) | P (s) | D (ms) +------------+------------+------------+
| | | | UpstreamRR | DirectRR | DirectCS |
+----------+---------+----------+------------+------------+------------+
+----------+---------+----------+------------+------------+------------+
| | | 50 | 1.94 | 1.96 | 1.96 |
| | +----------+------------+------------+------------+
| | | 100 | 1.94 | 1.96 | 1.96 |
| | 6 +----------+------------+------------+------------+
| | | 200 | 0.98 | 1.96 | 1.96 |
| | +----------+------------+------------+------------+
| | | 400 | 0.50 | 1.96 | 1.96 |
| 5 +---------+----------+------------+------------+------------+
| | | 50 | 1.93 | 1.98 | 1.98 |
| | +----------+------------+------------+------------+
| | | 100 | 1.86 | 1.98 | 1.98 |
| | 24 +----------+------------+------------+------------+
| | | 200 | 0.94 | 1.98 | 1.98 |
| | +----------+------------+------------+------------+
| | | 400 | 0.50 | 1.98 | 1.98 |
+----------+---------+----------+------------+------------+------------+
| | | 50 | 1.96 | 1.98 | 1.98 |
| | +----------+------------+------------+------------+
| | | 100 | 1.94 | 1.98 | 1.98 |
| | 6 +----------+------------+------------+------------+
| | | 200 | 1.94 | 1.98 | 1.98 |
| | +----------+------------+------------+------------+
| | | 400 | 0.50 | 1.98 | 1.98 |
| 100 +---------+----------+------------+------------+------------+
| | | 50 | 1.96 | 1.98 | 1.98 |
| | +----------+------------+------------+------------+
| | | 100 | 1.96 | 1.98 | 1.98 |
| | 24 +----------+------------+------------+------------+
| | | 200 | 1.88 | 1.98 | 1.98 |
| | +----------+------------+------------+------------+
| | | 400 | 0.50 | 1.98 | 1.98 |
+----------+---------+----------+------------+------------+------------+
Figure 2: The average played quality as a function of client
bandwidth B, client buffer size P and one-way delay D
Results on start-up delay are depicted in Figure 3. As the results
are minimally influenced by the available bandwidth B and client
buffer P, start-up delays are only shown for B equal to 5Mbps and P
equal to 6s.
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+----------+--------------------------------------+
| | Start-up delay (s) |
| D (ms) +------------+------------+------------+
| | UpstreamRR | DirectRR | DirectCS |
+----------+------------+------------+------------+
| 50 | 0.90 | 0.58 | 0.47 |
+----------+------------+------------+------------+
| 100 | 1.10 | 0.58 | 0.47 |
+----------+------------+------------+------------+
| 200 | 1.50 | 0.58 | 0.47 |
+----------+------------+------------+------------+
| 400 | 2.30 | 0.58 | 0.47 |
+----------+------------+------------+------------+
Figure 3: The start-up delay as a function of one-way delay D, for B
= 5Mbps and P = 6s
In line with the played quality, start-up delay is not negatively
influenced by an increasing network delay between the interconnected
CDNs when using the DirectRR and DirectCS policies. However, when
using the UpstreamRR policy, the start-up delay increases linearly
with the network delay D. Note that this start-up delay occurs
whenever a new stream is requested. This occurs, for example, when
switching channels in Internet TV scenarios as well as when users
skips parts of a movie in a Video on Demand scenario.
4. Conclusion
In this document, we proposed, evaluated and compared several
policies for routing requests and retrieving HAS content chunks
distributed across multiple interconnected CDNs. Concretely, the
traditional policy, herein called UpstreamRR, in which the original
CDN's request router dynamically redirects the end-users towards the
CDN currently hosting the requested content, is compared to two novel
policies, called DirectRR and DirectCS. These novel policies employ
HAS Manifest File rewriting to directly point end-users to the
correct CDN (DirectRR) or even the correct content server (DirectCS).
A thorough evaluation, based on NS-3 simulation results, was
conducted. It shows that the end-user QoE suffers greatly as a
consequence of the HTTP redirects that occur when employing the
standard UpstreamRR policy. Depending on the available bandwidth,
QoE degradation can start occurring when the one-way network delay
towards the upstream CDN is greater than 100 milliseconds. In
contrast, the reported results also show that the novel DirectRR and
DirectCS policies perform well under increasing network delays.
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In summary, these results prove the need for advanced request routing
mechanisms, as well as extensive cooperation between interconnected
CDNs, to be able to satisfy end-user quality requirements of state-
of-the-art HAS-based services.
5. Security Considerations
Not applicable.
6. References
6.1. Normative References
[I-D.brandenburg-cdni-has]
Brandenburg, R., Deventer, O., Faucheur, F., and K. Leung,
"Models for adaptive-streaming-aware CDN Interconnection",
draft-brandenburg-cdni-has-03 (work in progress),
July 2012.
6.2. Informative References
[msscode] "Microsoft's SmoothStreaming rate adaptation algorithm v1
source code", .
[ns3] "NS-3 discrete event network simulator",
.
[nsc] "Network Simulation Cradle",
.
Authors' Addresses
Jeroen Famaey
Ghent University - IBBT
Gaston Crommenlaan 8/201
Ghent 9050
Belgium
Phone: +32 9 331 49 38
Email: jeroen.famaey@intec.ugent.be
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Steven Latre
Ghent University - IBBT
Gaston Crommenlaan 8/201
Ghent 9050
Belgium
Phone: +32 9 331 49 88
Email: steven.latre@intec.ugent.be
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