Exploiting Proxy-Based Transcoding to Increase the

User Quality of Experience in Networked Applications

Maarten WijnantsPatrick Monsieurs

Peter QuaxWim Lamotte

Overview Introduction Intelligent Proxy Architecture

Application and Network Awareness Video Transcoding Plug-in

Sample NVE application Experimental Results Conclusions Future Work Questions

Introduction Increasing heterogeneity in end-user

device space PC, PDA, smartphone, ... each with their own capabilities and constraints

Heterogeneity complicates multimedia content delivery i.e. displaying MM content on PC screen

vs PDA screen Possible solutions

Providing specialized versions of content On-the-fly content transcoding

Introduction Supplying specialized versions of content

users receive version that best suits the capabilities of their client device and network connection

lacks flexibility complicates content management

On-the-fly content transcoding content is transformed to a convenient

format before it reaches the end-user flexible solution only high quality content on server however: computational complex

Introduction Usability of transcoding is not confined to

content delivery scenarios We discuss the implementation of a novel

plug-in that adds transcoding functionality to our previously introduced intelligent proxy

Can our transcoding-enabled proxy positively affect the user Quality of Experience (QoE) in networked applications?

Intelligent Proxy Architecture Our intelligent proxies are application

aware client application is enhanced with a “Network

Intelligence Layer” the NILayer continuously queries the

application's awareness management model retrieved information about the relative

importance of different application data streams is sent to proxy

NILayer is highly reusable enables easy integration of our proxy

system in many networked applications

Intelligent Proxy Architecture Our intelligent proxies are also network

aware proxy periodically probes the network links

going to connected clients latency throughput packet loss rate

proxy records bandwidth usage of every data stream that passes through it

Intelligent Proxy Architecture Based on their compound awareness, our

proxies intelligently manage each client's available bandwidth suppose a client's downstream bandwidth no

longer suffices to receive all streams at maximum quality

proxy will determine which streams should be reduced in quality or even blocked

We position our proxies close to end-users Stream management complexity is

moved to the edge of the network

Video Transcoding Plug-in Our proxies are very generic

by default, the proxy can execute only basic operations on data streams

Proxies are equipped with a plug-in mechanism can be used to extend proxy performance and

functionality This approach ensures that our

proxies can be integrated in many networked applications and attain a high level of performance in all these situations

Video Transcoding Plug-in To add more fine-grained stream control to

our proxy architecture, we implemented a video transcoding plug-in plug-in enables the proxy to transcode video

streams to lower quality by reducing video bitrate spatial or temporal resolution

uses the cascaded pixel-domain transcoding approach

not very efficient best results in terms of image quality

Sample NVE application We tested our proxy architecture by

integrating it into our in-house developed multi-user NVE framework focuses on scalability

by maximizing client responsibilities by relying on direct client-to-client multicast

communication tries to increase the

immersive experience by supporting video-based avatars

Sample NVE application Technical details of the NVE framework

virtual world is divided into regions each region has a unique MC address event information is sent only to the MC address of the

originating region Area of Interest manager selects the regions a

user should be aware of limits the amount of information clients need to

receive and process virtual world is also divided into video

regions each video region has 3 MC addresses video-based avatars send out 3 distinct video

qualities (high, medium and low)

Sample NVE application Technical aspects of the NVE framework

video qualities used by the framework

like the AoI manager, the Video Area of Interest (VAoI) manager decides which video MC addresses the client should subscribe to

High Quality Medium Quality Low Quality

Codec H263 H263 H263

Resolution CIF (352x288) CIF (352x288) CIF (352x288)

FPS 25 15 15

Bitrate 200.000 100.000 50.000

Experimental Results Integrating our proxy architecture in the

NVE framework proved to be easy inserting the NILayer into the client software

was straightforward transcoding plug-in had to be tailored to the

framework

Experimental Results Description of the experiment

4 clients running the unmodified framework 2 clients connected through our transcoding-

enabled proxy clients C1, C2 and C3

were represented as video-based avatars

available downstream bandwidth of clients PA and PB was varied artificially over time

all clients remained stationary

Experimental Results Video network traffic received by client PA

Experimental Results Video network traffic received by client PB

Experimental Results Video network traffic received by client C4

Experimental Results What does this experiment learn us?

clients PA and PB both roughly stayed within their bandwidth limitations

proxy exploits its application awareness to intelligently decide which video streams should be transcoded to a lower quality

if the world is populated solely by clients connected through our proxy system, video-based clients only need to send HQ video

less client processor load asymmetric nature of most current Internet

subscriptions

Experimental Results Main drawback of the video transcoding

plug-in is its computational complexity transcoding performance was not one of our

main objectives we nonetheless wanted the number of clients

our proxy can support simultaneously to be as high as possible

Transcoding plug-in is equipped withan intelligent scaling mechanism if the proxy's average processor usage

exceeds a predefined threshold, MQ transcoding is disabled

Experimental Results The intelligent scaling mechanism can

decrease the proxy’s processor load by a factor of two approximately

Conclusions We have presented a proxy architecture

that is both application and network aware Our transcoding-enabled proxy at all times

exploits all available client bandwidth without ever exceeding it, and intelligently and dynamically distributes this bandwidth over all involved network streams in order to optimize the user QoE

scarce client upstream bandwidth is no longer wasted

Future Work Add device awareness to our intelligent

proxy architecture make more complex transcoding decisions distribute client bandwidth even more

efficiently Increase the performance and scalability of

our transcoding plug-in Add transcoding functionality for

data other than video (e.g. audio) Perform more elaborate experiments

Questions?

Additional Results

Additional Results