Internet DRAFT - draft-khasnabish-dispatch-qoe-management
draft-khasnabish-dispatch-qoe-management
DISPATCH WG B. Khasnabish
Internet-Draft ZTE USA, Inc.
Intended status: Informational G. Fernando
Expires: January 8, 2014 Compression Labs, Inc.
Y. Lin
ZTE Corporation
July 7, 2013
End-point based Multimedia QoE Management
draft-khasnabish-dispatch-qoe-management-02
Abstract
This draft describes a method for improving the quality of experience
(QoE) for real-time video and other multimedia services using
features and functions of the end-point only, that is, without
requiring any upgrade to the network transport infrastructure. Any
upgrade to the network transport infrastructure not only incurs
significant costs, these are also time consuming and technology-
dependent. Therefore, these QoE improvement mechanisms are
significantly more attractive to both network operators and service
providers.
Status of this Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on January 8, 2014.
Copyright Notice
Copyright (c) 2013 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
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(http://trustee.ietf.org/license-info) in effect on the date of
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1. Method of controlling QoE for real-time video and
other multimedia services . . . . . . . . . . . . . . . . 4
2. Conventions used in this document . . . . . . . . . . . . . . 5
3. Preliminary Survey of existing QoE methods . . . . . . . . . . 6
3.1. Measurement Techniques for Network Quality . . . . . . . . 6
3.1.1. Network-based measurements . . . . . . . . . . . . . . 6
3.1.2. Content Inspection . . . . . . . . . . . . . . . . . . 7
3.1.2.1. Audio/Video Content Analysis . . . . . . . . . . . 7
3.1.2.2. Other Analysis Techniques at the Bitstream
level . . . . . . . . . . . . . . . . . . . . . . 7
3.2. Metrics Used for QoE Assessment . . . . . . . . . . . . . 7
3.2.1. Direct Metrics . . . . . . . . . . . . . . . . . . . . 7
3.2.2. Indirect Metrics . . . . . . . . . . . . . . . . . . . 8
4. Proposed Toolkit for Managing QoE . . . . . . . . . . . . . . 8
4.1. Multi-layer Elastic Virtualized Buffer Stack . . . . . . . 12
4.2. Jitter Buffer . . . . . . . . . . . . . . . . . . . . . . 12
4.3. Error resilience and concealment methods . . . . . . . . . 12
4.4. Transport rate clinging . . . . . . . . . . . . . . . . . 13
4.5. Transport rate adaption . . . . . . . . . . . . . . . . . 13
4.6. Endpoint Resource Reallocation . . . . . . . . . . . . . . 13
4.7. Adaptation . . . . . . . . . . . . . . . . . . . . . . . . 15
4.8. Virtualized displays . . . . . . . . . . . . . . . . . . . 15
4.9. Use of trick play methods . . . . . . . . . . . . . . . . 15
4.10. Synchronization in multicast . . . . . . . . . . . . . . . 15
5. Security considerations . . . . . . . . . . . . . . . . . . . 16
6. IANA considerations . . . . . . . . . . . . . . . . . . . . . 16
7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 16
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 16
9. References . . . . . . . . . . . . . . . . . . . . . . . . . . 16
9.1. Normative References . . . . . . . . . . . . . . . . . . . 16
9.2. Informative References . . . . . . . . . . . . . . . . . . 16
Appendix A. Appendix . . . . . . . . . . . . . . . . . . . . . . 17
A.1. Factors Influencing QoE . . . . . . . . . . . . . . . . . 17
A.1.1. Service . . . . . . . . . . . . . . . . . . . . . . . 17
A.1.2. Content . . . . . . . . . . . . . . . . . . . . . . . 17
A.1.3. Terminal Device Used for Consuming Content . . . . . . 17
A.1.4. View/Listener Characteristics . . . . . . . . . . . . 17
A.2. Range of Network Architectures . . . . . . . . . . . . . . 18
A.2.1. Managed vs. Unmanaged Networks . . . . . . . . . . . . 18
A.2.2. Unicast vs. Multicast Delivery . . . . . . . . . . . . 18
A.2.3. Range of Service Offerings . . . . . . . . . . . . . . 18
A.2.3.1. Traditional Closed Network operators . . . . . . . 18
A.2.3.2. Over-the-Top Service Offerings . . . . . . . . . . 18
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 19
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1. Introduction
This Internet Draft describes a method for improving the quality of
experience (QoE) for real-time video and other multimedia services
without requiring any upgrade to the network transport
infrastructure.
It is recognized that network quality of service (QoS) based
management of multimedia services has a very valid role. However,
such management techniques are orthogonal to endpoint based QoE
management, and thus are outside the scope of this Internet Draft.
This Internet Draft defines a common set of QoE parameters that are
applicable for HTTP, Websocket or RTP sessions. Hence, these
parameters would be used for controlling the QoE for any real-time
video and other session-based multimedia services over an Internet-
protocol (IP) based network. The multimedia session may be displayed
on a mobile communication terminal, a tablet/phablet, a laptop, a
television, etc. This method facilitates a high-quality user
experience with minimal user input for interactively controlling the
QoE. Any user input may be through a touch sensitive device or
verbal commands. This method may be applicable for improving QoE for
both multicast and OTT (over the top) service scenarios, and may
apply equally to transit/intermediate network elements.
Depending on the particular protocol (RTP/UDP vs. HTTP/TCP) different
tools from the toolkit may be applied.
1.1. Method of controlling QoE for real-time video and other multimedia
services
Data transport protocols for the Internet have been designed to be
agnostic to the data type. There has been minimal attention given to
the requirements for time-critical and high priority services, such
as real-time communications, etc. This has lead to such services
providing unpredictable and inconsistent user experiences, and
thereby leading to lost revenue for the service provider.
Network architects have often used quality of service (QoS) as the
metric for objectively determining the level of service to be
provided. From a customer perspective the QoS measure is not
satisfactory as it does not take into consideration the subjective
experience; instead it is necessary to measure the quality of
experience (QoE). QoE is the user experience that can be quantified
in terms of the subjective experience, and it depends on various
factors, including the type of content, expectations of the consumer
of the content, the device on which the content is -consumed- and the
environment in which the content is consumed. Admittedly, these are
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indeed subjective measures. However, there are standardization
efforts (in particular in ITU-T) to evaluate and quantify QoE as
there is a real need for such quantitative metrics by service
providers.
This Internet Draft proposes a method for transport impairment
independent control of QoE for multimedia services. The display of
the multimedia session could be in a mobile communication terminal, a
tablet, a laptop, a television, etc. This proposal relates to
facilitating high-quality user experience with minimal user input
(could be through a touch sensitive device or a verbal command) for
interactively controlling the QoE. This method is applicable to
operator managed services and to unmanaged (i.e., OTT - over the top)
service. Additionally, this may apply to intermediate network
elements as well. The focus of this proposal is for the QoE
management to be transport independent, and hence it is applicable to
a range of media transports, including HTTP, WebSocket or RTP
sessions.
In order to improve quality it is common practice to focus on
improving network infrastructure (bandwidth increase, etc.).
However, our proposal enables improvements in quality by utilizing
transport independent QoE management.
2. Conventions used in this document
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC-2119 [RFC2119].
In this document, these words will appear with that interpretation
only when in ALL CAPS. Lower case uses of these words are not to be
interpreted as carrying RFC-2119 significance.
A list of acronyms and abbreviations used in this document are
presented below.
o ARQ: Automatic Repeat ReQuest
o ECC: Error Correction Coding / Elastic Coding and Compensation
o FEC: Forward Error Correction
o MEP: Media Encapsulation and Packetization
o MOS: Mean Opinion Score
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o MRD: Media Resources Description / Management of Resources
Distribution
o OTT: Over The Top
o PLC: Packet Loss Concealment
o QoE: Quality of Experience
o QoS: Quality of Service
o RPP: Resources Pre-Positioning Policy
o RTP: Real-time Transport Protocol
o RTT: Round-Trip delay Time
o UEP: Unequal Error Correction
o XIF: Transport Independent Fashion
3. Preliminary Survey of existing QoE methods
3.1. Measurement Techniques for Network Quality
Currently there are two measurement techniques: (a) Network-based
Measurement, and (b)Content Inspection.
ITU-T and other standards bodies have been developing standards to
address QoE measurement in the area of multimedia/IPTV [2], [3].
Below, these measurement techniques have been categorized. These
techniques vary according to the performance, complexity and
feasibility. It is left to service providers and network operators
to determine which of these to be used, and how to combine these
according to different needs, multimedia content type, network, end
user equipment and service type.
3.1.1. Network-based measurements
These are objective network metrics which thus do not require
accessing and inspecting the content. These metrics (one-way delay,
packet loss and jitter) are uses in QoS assessment as well. However,
in the context of QoE the intent is to predict multimedia quality
based on these metrics.
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3.1.2. Content Inspection
Content inspection is applied at various levels, and these are
described below.
3.1.2.1. Audio/Video Content Analysis
There are objective and subjective content analysis techniques that
are used to determine the distortion that may be introduced at a
given stage in the end-to-end multimedia delivery system. These
content analysis techniques may be based on the following approaches:
(a) Non-reference (NR)-- the NR approaches assess quality without
knowledge of the original source, (b) Reduced-reference (RR) -- the
RR approach uses an alternative channel to send parameters
corresponding to the delivered content, thus enabling evaluation of
content quality, and (c) Full-reference (FR) -- the FR method
requires the original content to be available in order to assess
quality. Hence, this approach is not practical for most delivery
scenarios.
3.1.2.2. Other Analysis Techniques at the Bitstream level
By inspection of the bitstream it is possible to extract the
following parameters from the headers that can be used to assess
quality: (a) Timestamp accuracy/error, (b) PCR jitter/clock accuracy,
(c) Media Encapsulation and Packetization (MEP) Header. The above
parameters require deep packet inspection, but they do not require
decoding of the audio/video sequences
3.2. Metrics Used for QoE Assessment
In this section we shall provide details of metrics for QoE
assessment that are currently used in the industry. In [4] the
metrics used for QoE assessment have been categorized as being either
-direct- or -indirect-. These will be described below.
3.2.1. Direct Metrics
These metrics directly affect the user's perception of the audio/
video experience. peak signal to noise ratio (PSNR), structural
similarity (SSIM) and video quality metric (VQM) are three commonly
used objective metrics for quality analysis. For subjective analysis
the commonly used methodology is the ITU-T Recommendation BT500 [5].
ITU-T have defined the mean opinion score (MOS)[6] which is a meta-
metric which uses values form several other metrics. Due to the
cumbersome nature of subjective analysis techniques there has been
much work done to map objective metrics to MOS, for example, there's
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a mapping of PSNR to MOS.
3.2.2. Indirect Metrics
There are indirect metrics which do not directly correlate to the
multimedia content quality. Instead they correspond to artifacts
that determine the user's satisfaction of the multimedia service.
These indirect metrics include the following.
o Responsiveness to user requests -- time delay from user request to
response by the system. Example -- responsiveness to pausing
video.
o Start-up time -- time delay from user requesting content to
receiving the content.
o Delivery synchronization -- when several users access a given
content do they all receive the content at the same time?
o Live content delay -- time delay from content being available at
the encoder to it being received by the user. For live streaming
this is an important requirement. This is applicable to
progressive downloading as well.
o Picture freezing -- due to mismanagement of buffers. One example
is buffer underflow.
o Multimedia synchronization -- the accuracy at which audio, video
and associated data (including subtitles) are synchronized has a
significant impact on the QoE. For example, if audio is earlier
or later than video by 160ms, then this will lower the QoE.
o Content/Channel Switching time -- time delay from the user
requesting content/channel switching to the display of the
requested content.
o Blocking artifact -- consistency of the data in one frame.
o Mosaic -- if packet is lost during transport, and it can not be
recovered by the client, mosaic will appear.
4. Proposed Toolkit for Managing QoE
We propose a toolkit for managing QoE for a multimedia system.
P.NBAMS [2] is a quality assessment model that uses bitstream
information in addition to prior knowledge of the media stream as
well as client buffer information. P.NAMS [3] is another quality
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assessment model that uses only prior knowledge of the media stream
as well as the client buffer information. In both of these
Recommendations Figure 1e illustrates the "Embedded operation mode"
where QoE management is performed at the client/end-point.
Our proposal similarly aims to perform QoE management at the client/
end-point and thus it can be described as being performed in a
Transport Independent Fashion (XIF). Once a session starts with a
specific transport bandwidth, the endpoint's objective is to maintain
persistently a consistent QoE even when the session bandwidth
fluctuates. The smartness or intelligence resides at the endpoint,
and the use of virtualization makes the simplistic implementation of
the operation a technically feasible one. This is shown in Figure-1
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+------------------------------------------------------------------+
|/----------\ Endpoint management agent |
|| |+---------------------------------------------------+ |
|| || QoE/MOS ctl | |
|| +---------------------------/ | |
||Present- || | | |
|| ation ||QoE/ | | |
|| agent ||MOS +-----------+ +-----\------+ /----------\ | |
|| ||ctl | Decoding | | QoE/MOS | | | | |
||(Audio, +------+ and | | | | Storage | | |
|| Video, || | control +--+ model +---+ | | |
|| Text, +------+ | | | | | | |
|| etc.) ||Final+-----+-----+ +-----+------+ \----+-----/ | |
|| ||media |Refined media | | MRD/ | |
|| ||stream |streams | | RPP | |
|| || +------+--------------+---------------+-----+ | |
|\----------/| | Physical/Virtual buffer and QoE/MOS | | |
| | | management agent (with a multitude of | | |
| | | tools in toolkit | | |
| | | *Multilayer elastic virtualized buf. stack| | |
| | | *Jitter buffer | | |
| | | *Error correction and concealment | | |
| | | *Transport rate clinging | | |
| | | *Transport rate adaptation | | |
| | | *Endpoint resource allocation(among audio,| | |
| | | video, message, etc.) | | |
| | | *Depth adaptation | | |
| | | *Virtualized display | | |
| | | *Synchronization in multicast | | |
| | | *Trick-play methods(Slow/Fast, | | |
| | | Look-ahead/Reverse, etc. | | |
| | +------------------/------------------------+ | |
| +-----------------------|---------------------------+ |
+------------------------------------|-----------------------------+
|Raw
|media
|stream
_,..\..,,
_-` `',
/ \
| Network |
| |
\ /
`-, ,-`
``''--'``
Figure 1: QoE management at the client/end-point in a Transport
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Independent Fashion (XIF)
Media content is received over an IP based network. However, it is
expected that the actual transport would include any of the following
-- RTP/UDP, HTTP/TCP, HTTP/UDP, etc. HTTP/UDP is relevant if the
roundtrip link condition is poor or RTT (round-trip delay time) is
long, etc. A QoE Management Agent in the endpoint will receive the
media content. The management agent has a toolkit of "tools" which
will be used to maintain the QoE. This toolkit includes the
following tools
o Multi-layer Elastic Virtualized Buffer Stack
o Jitter Buffer
o Error resilience methods
o Transport Rate Clinging
o Transport rate adaption
o Endpoint Resource Reallocation (among audio, video, messaging,
etc. services)
o Adaptation, e.g., depth for image, surroundings of sound, etc.
o Virtualized Display
o Use of trick play methods
o Synchronization in multicast
Each of these shall be described in detail further down in this
section. However, it is noted that there may be other tools which
could also lead towards improving QoE. Any such tools may also be
added as appropriate. With the aid of these tools the QoE management
agent will maintain the QoE based on policy as set for the given
endpoint. Resource pre-positioning policy information will be
available in the local database. The QoE model will be applied to
determine the QoE, and the metrics will be signaled to the
presentation agent. In parallel with QoE evaluation, the media which
has been "refined" by the QoE management agent is sent to the
decoding and control agent where the content is decoded. The decoded
data is then sent to the presentation agent. The decoding and
control agent receives QoE signal information from the presentation
agent. With this information the decoding and control agent is able
to apply any remedial steps in order to maintain QoE.
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4.1. Multi-layer Elastic Virtualized Buffer Stack
Virtualization of buffer allows increase of the effective available
buffer space (depth) over the amount that is actually physically
available. This can be achieved, for example, by assigning
temporarily larger than actually required physical buffer/memory
chunk so that during process execution/operation a larger memory
block can be temporarily used (must make sure that the allocation/
operations do not overlap or interfere with each other, as required
by virtualization). This helps improve performance without extra
costs. This is equivalent to vertical expansion of the buffer space.
When "Elasticity" is added to the virtualized buffer, it allows
incorporation of Elastic behavior (i.e. capability to expand and
contract seamlessly in order to maintain a certain output rate) in
the operation of the buffer module. This is equivalent to horizontal
expansion of the buffer space.
4.2. Jitter Buffer
Jitter is the variation of packet latency over a network. The
severity of jitter can vary significantly depending on network type
and current conditions. Therefore, a device called jitter buffer is
commonly introduced in the receiver. The jitter buffer can de-jitter
the incoming stream of packets and provide a constant flow of data to
the decoder.
4.3. Error resilience and concealment methods
Packet loss is due to either random loss and network congestion. In
first situation, error resilience methods including Automatic Repeat
reQuest (ARQ) and Forward Error Correction (FEC) may also be used to
maintain QoE. Unequal Error Correction (UEP) which is based on FEC
may be more commonly used. The original data can be classified into
several levels, the most important data has highest priority.
Different priority has different redundancy.
With network congestion, ARQ and FEC are not suitable as they could
make the situation worse. Hence, different measures should be
adopted according to network characteristics. When receiving
multimedia communication payloads, the receiver may evaluate network
statistics, including packet loss , consecutive packet loss, delay,
jitter etc. from this data it is possible to determine if the network
is congested. The receiver sends these parameters to the sender, and
the sender can adjust the packet delivery strategy in real time based
on these parameters: if the network is congested, sender can modify
it's encode rate or send rate to decrease congestion, and make sure
the protected data from FEC or ARQ is under the total rate.
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Moreover, the network condition is unknown in the initial state of
the communication, then sender may take its strategy supposing the
network condition is poor. Packet Loss Concealment (PLC) is another
tool that may be used for this purpose. The other method is using
two or more encoders. When one frame is lost, the frame from another
encoder can be used. It is important to process these two streams
switchover. The delay of the encoders should be known for
synchronization. Mute frame can be added to align the start time of
frames. When switching between two streams, smooth the joins of
different frames.
4.4. Transport rate clinging
The intent of transport rate clinging is to maintain a steady rate of
bit stream (e.g., media). The brute force method is to introduce
blank packets in the event the required media data rate goes lower
than a given threshold. Instead of using this brute force method, it
is possible to reallocate the bandwidth to other sub-processes
through appropriate virtualization.
4.5. Transport rate adaption
During multimedia transport, the network may not be stable. The
available bandwidth may be time-varing. In order to maintain a
consistent QoE, transport rate should change according to the
available bandwidth. If the transport rate is too high, packet loss
will occur. Otherwise, bandwidth resource is waste.
4.6. Endpoint Resource Reallocation
Endpoint resource reallocation involves dynamically adjusting
virtualized resources among sub-sessions, audio, video, text/
messaging, etc. The aim is to ensure that these different types of
sub-sessions maintain a consistent QoE. A flowchart for dynamically
adjusting virtualized resources among sub-sessions (audio, video,
text/messaging, etc.) is presented in Figure 2.
+----------+
| Start |
+----/-----+
|
|
|
+---------------------------------\-------------------------------+
| |
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| +--------+ |
| |Local | +----------------+ |
| |RPP |------Historic trend | |
| | | |based session- |---> +---------------------+ |
| +--------+ |specific res. | | |-------------------- | |
| |allocation | | | Projected resource | |
| +----------------+ | |requirements for next| |
|+-------------+ |-->| few time intervals/ | |
||Res. utiliz. | | | periods for | |
||monitor | /-----------------\ | | maintaining | |
||(trick-play, | |Current resource | | | consistent QoE | |
|| ECC, | |utilization | | +---------------------+ |
|| rate adjust-| |trends & reqs. |--> | ` |
|| ment,...)| | for managing | | +---'--+ |
|| |-| QoE | | |MRD/ | |
|+-------------+ \-----------------/ | |RPP | |
| | +------+ |
+-------------------------------------------------|---------------+
/--------------------------------\--/
| |
| |
\, \,
.'` `., .'` .,
,-` ', ,-` ',
.` `', ,.` Procure ',
.'`Distribution of '`, -' resources from ',.
,-` is sufficient for ', NO ,`MRD/RPP for adjustment',
-, the desired QoE ----->, for resource allocation .
`', ,-` `', among sessions ,-`
`'. ,-` `'. ,-`
`'., .-` `'., .-`
'., _.'` '., _'`
`/' `/'
| |
YES | DONE |
| |
+------\-------------------------------------\----+
| Request for additional resources |
| for maintaining overall QoE |
| is fulfilled |
| |
+-------------------------/-----------------------+
|
|
/-----\------\
| END |
| |
\------------/
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Figure 2: A flowchart for dynamically adjusting virtualized resources
among sub-sessions
4.7. Adaptation
Adaptation (of image/picture depth) requirements may depend on the
type of scene/picture, e.g., Talking head, sports, action movie, and
so on. The number of GOPs/frames required to recover from any losses
would depend on the type of scene/picture.
4.8. Virtualized displays
The goal here is to manage the real-estate of the screen. Depending
on the intended resolution and screen size at which a given piece of
media content is generated there is some opportunity to maintain the
QoE for, say, a lower sized display.
4.9. Use of trick play methods
Various mechanisms from trick play can be utilized for slow/fast and
Look-Ahead/Reverse adjustment of the scene. Such methods provide the
means to catch up with "real-time" in the event that there has been a
major hiccup in delivery. Voice recognition may be used to determine
if catch up with "real-time" is required. However, if network
condition or the environment of the endpoint is too poor to guarantee
the quality of voice data, the sender can generate text message from
the actual voice by voice recognition module, and send text message
to receiver. Network condition can feedback by packet loss, jitter,
delay etc. The environment of the endpoint include voice output
device, ambient noise, and so on. The receiver may choose to
directly present the text message, or it can use a text-to-speech
module to reconstruct the audio signal, and then present it.
4.10. Synchronization in multicast
In multicast system, the server usually send I-frames or
independently decodable frames periodically, the endpoint system
display may be out of sync because of the different access times. A
re-encode module can be added to the multicast system where it backs
up the non-I frames from multicast server and re-encode them to new I
frames, these new I frames use smaller bandwidth than the original I
frames . When client join multicast group, it send request to
server, the server can choose the latest I frame, send it and the
following frames to client. Meanwhile, the server send the
information to tell the client how to display, including the started
time of the first I frame and the distance to the current frame which
is send to other clients that already in the multicast group, then
client can play these frames quickly until synchronize with other
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clients.
5. Security considerations
TBD
6. IANA considerations
This Internet Draft includes no request to IANA.
7. Conclusions
We have presented a tool-kit based approach for improving the quality
of experience (QoE) for video and other multi-media services in a
transport impairment independent fashion (XIF). This method is both
flexible and expandable. As the technologies evolve, the existing
techniques (in the tool-kit) can be updated, and many other new and
improved techniques can be easily incorporated in the tool-box
without incurring any significant overheads.
8. Acknowledgements
The authors would like to thank Mary Barnes and Roni Even for
encouraging discussions and guidance. The authors also wish to thank
Romans Krzanowski for reviewing and providing comments on version 0
of the Internet Draft.
9. References
9.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels, BCP 14", March 1997.
9.2. Informative References
[1] ITU-T, Rec., "P.NAMS, Non-intrusive parametric model for
the Assessment of performance of Multimedia Streaming",
November 2009.
[2] ITU-T, Rec., "P.NBAMS, Non-intrusive bitstream model for
the Assessment of performance of Multimedia Streaming",
January 2011.
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[3] Serral-Graci, A. and R. Barlet , "An Overview of Quality
of Experience Measurement Challenges for Video
Applications in IP Networks, 8th International Conference
on Wired/Wireless Internet Communications (WWIC)",
June 2010.
[4] ITU-T, Rec., "Recommendation, BT 500", January 2011.
[5] ITU-T, Rec., "P.800, Recommendation", August 1996.
Appendix A. Appendix
A.1. Factors Influencing QoE
The QoE depends on several factors. This includes the type of
service, type of content and the terminal device intended for use of
the content.
A.1.1. Service
For any given entertainment service there is a specific minimum level
of service expected by the viewer. This would determine the MOS.
One could generalize and state that if a payment is made for an
entertainment service then there is a much higher expectation of QoE
than if it were to be a "free" service. In the free service category
one would also include ad-driven services where the viewer's QoE
expectations are lower.
A.1.2. Content
The type of content will influence the user's QoE expectations. The
requirements for drama are different to those for sports content.
The QoS parameters contributing towards the MOS would be different
depending on the type of content.
A.1.3. Terminal Device Used for Consuming Content
The viewer's QoE expectations vary depending on the terminal device
used for viewing the content. For example, the expectations of a
viewer would be much higher if the content were being viewed on a 50-
inch HDTV display as opposed to on a 4-inch smart phone screen.
A.1.4. View/Listener Characteristics
Each human view or listener can have a different impact on the QoE
measurement. In order to make the QoE measurement practical from an
operations perspective it is important to take this (impact of the
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listener and viewer) out of the QoE measurement. This can be done by
taking as wide a sample of viewers and listeners in the MOS
calculation stage. [See ITU-T Ref.]
A.2. Range of Network Architectures
TBD
A.2.1. Managed vs. Unmanaged Networks
Today with network based media services there is a clear distinction
made between how such services are provided depending on whether it
is over a managed or unmanaged network. A managed network has the
ability to configure, manage and monitor the network, thereby
enabling greater control over how data is transported, and who has
access to the data. It is also possible to generalize to some extent
by stating that managed networks support reservation of bandwidth for
each user. Unmanaged networks, by implication, do not have such
reservation capabilities.
A.2.2. Unicast vs. Multicast Delivery
Unicast delivery services pose less of a problem with respect to
maintaining QoE when compared to multicast delivery. The problems
experiences with multicast delivery can be as complex as those for
unmanaged networks. This document will focus on both forms of
delivery -- unicast and multicast, as well as on managed and
unmanaged networks.
A.2.3. Range of Service Offerings
A.2.3.1. Traditional Closed Network operators
Traditionally, network operators, such as cable MSOs, satellite
operators, "Telcos" and terrestrial operators have, controlled the
networks over which services are provided. They either own the
network infrastructure, or they have close business relationships
with the owners of the network infrastructure. Starting from
traditional (i.e., non-IP) delivery methods they have migrated to
providing IPTV services. Other than the fact that IP and invariably
UDP protocols have been introduced to the network stack there has
been no fundamental shift in the service offerings.
A.2.3.2. Over-the-Top Service Offerings
More recently, companies like Netflix and Apple have started to
provide media service to subscribers using network infrastructures
which are neither owned or in which they have any business
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relationship. These services are termed "over-the-top." The
traditional network operators (cable, satellite, Telco and
terrestrial) have also started to provide over-the-top media
services. These over-the-top media services use broadband delivery,
and for the traditional network operators this is a component of
their overall offering. Over-the-top services cannot assume any
reservation of bandwidth, and hence such services are provided over
unmanaged networks.
Authors' Addresses
Bhumip Khasnabish
ZTE USA, Inc.
55 Madison Avenue, Suite 160
Morristown, New Jersey 07960
USA
Phone: +001-781-752-8003
Email: vumip1@gmail.com, bhumip.khasnabish@zteusa.com
Gerard Fernando
Compression Labs, Inc.
303, Twin Dolphin Drive, Suite 600
Redwood City, CA 94065
USA
Phone: +1-650-704-9862
Email: gerardmxf@yahoo.co.uk, gerard.fernando@compressionlabs.com
Ya Lin
ZTE Corporation
22/F, ZTE Research and Development Building, Nanshang District
Shenzhen 518057
P.R.China
Phone: +86-755-26776850
Email: lin.ya@zte.com.cn
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