Multimedia streaming technologies based on the Hypertext Transfer Protocol (HTTP) are very popular and used by many content providers such as Netflix, Hulu, and Vudu. Recently, ISO/IEC MPEG has ratified Dynamic Adaptive Streaming over HTTP (DASH) which extends the traditional HTTP streaming with an adaptive component addressing the issue of varying bandwidth conditions that users are facing in networks based on the Internet Protocol (IP). Additionally, industry has already deployed several solutions based on such an approach which simplifies large scale deployment because the whole streaming logic is located at the client. However, these features may introduce drawbacks when multiple clients compete for a network bottleneck due to the fact that the clients are not aware of the network infrastructure such as proxies or other clients. This paper identifies these negative effects and the evaluation thereof using MPEG-DASH and Microsoft Smooth Streaming. Furthermore, we propose a novel adaptation algorithm introducing the concept of fairness regarding a cluster of clients. In anticipation of the results we can conclude that we achieve more efficient bottleneck bandwidth utilization and less quality switches.

1. A PROXY EFFECT ANALYSIS AND FAIR
ADAPTATION ALGORITHM FOR MULTIPLE
COMPETING DYNAMIC ADAPTIVE STREAMING
OVER HTTP CLIENTS
Christopher Mueller, Stefan Lederer and Christian Timmerer
Alpen-Adria Universität Klagenfurt (AAU)  Faculty of Technical Sciences (TEWI)
Institute of Information Technology (ITEC)  Multimedia Communication (MMC)
VCIP12 - 29-11-2012
Christopher Mueller Proxy Effect Analysis and Fair Adaptation 1

2. OUTLINE
 Introduction
 Proxy Effect Analysis
 Experiments with multiple competing dynamic HTTP streaming
clients
 Testbed & Methodology
 Microsoft Smooth Streaming
 MPEG-DASH
 Fair Adaptation
 Conclusion
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3. DYNAMIC ADAPTIVE STREAMING
OVER HTTP – IN A NUTSHELL
Multiple Quality Levels Varying Bandwidth Conditions
 Dynamic adaption to the network conditions
Selects the appropriate
 Reuse of existing Internet infrastructure segments for each
 Logic is located at the client side timepoint
 Has the potential to play a major role in future networks
optimizations and problems analysis's are crucial
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4. MOTIVATION
 Real-Time Entertainment is currently accounting for more than 50% of
the whole internet traffic
 This traffic still grows and HTTP is one of the major protocols
 DASH has the potential to play a significant role in future networks
Large scale scenarios are realistic use cases in the next few years
 Proxy as a caching element
 Widely deployed in the internet
 Reduces upstream and downstream and therefore costs
 Almost every ISP or bigger institution e.g., university’s, companies etc.,
are using proxy servers
 Could fully transparent intercept the connection between the client and
the server
It could be assumed that nearly each HTTP connection is intercepted
by a proxy server
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5. PROXY EFFECT ANALYSIS
 Potential general problems and issues for large scale dynamic
streaming over HTTP scenarios
 Clients are not aware of the network infrastructure
 Clients are not aware of other clients
 Uncontrolled distribution of media content over caching proxies
 Usually only a portion of the content is cached
 No deep inspection of throughput measurements to specific
segments
A client could make an unfavorable adaptation decision
A client could negatively influence other clients
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6. PROXY EFFECT ANALYSIS - EXAMPLE
 HTTP Server provides content with two quality levels
 Base Quality 5 Mbps
 Enhancement Quality 7 Mbps
 The bottleneck bandwidth is restricted to 8 Mbps
 Client 1 could only select the base quality due to the restricted
bandwidth
 Client 2 could potentially select the enhancement quality
without client 1 6 Mbps
Client 1
8 Mbps
2
Client 1 Bandwidth
HTTP Server Proxy
Bottleneck Bandwidth 8 Mbps
Client 2
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7. PROXY EFFECT ANALYSIS - EXAMPLE
 Client 1 measures an average throughput of 6 Mbps and uses
the base quality which will be cached at the proxy
 Client 2 will also use the base quality at the beginning and
measure and average throughput of 8 Mbps
Client 2 will switch to the enhancement quality and the proxy
has to host two connections to the content server which will
be approx. shared in fair way (4 Mbps)
6 Mbps
Client 1
8 Mbps
HTTP Server Proxy
8 Mbps
Client 2
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8. PROXY EFFECT ANALYSIS - EXAMPLE
 Both clients will now measure an effective available
bandwidth of 4 Mbps
Client 2 will switch back to base quality and everything starts
from the beginning
 Problems
 Self caused frequent quality switching
 Potential unsmooth playback due to unfavorable adaptation
6 Mbps
Client 1
8 Mbps
HTTP Server Proxy
8 Mbps
Client 2
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9. METHODOLOGY AND EXPERIMENTAL
SETUP
 All experiments have been consistently performed with the
same settings:
 Content: Big Buck Bunny encoded with x264 at two bitrates e.g.,
700 kbps and 1300 kbps
 Proxy: Squid open source proxy in transparent mode
 Shaping: Linux traffic control and hierarchal token bucket system
 The server and client components differ only between the
MPEG-DASH and MSS experiment
Same content for all experiments
Stays the same over all experiments
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10. MICROSOFT SMOOTH STREAMING
 Server and Client Setup
 Server is based on Microsoft Windows Server 2008
 The clients are based on Microsoft Windows 7 and Silverlight
 Network Setup
 Bottleneck bandwidth has been set to 2200 kbps
 Client 1 bandwidth restricted at 1100 kbps Client 1 Bandwidth
Windows 7
 Client 2 bandwidth restricted at 2200 kbps
Windows Server 2008
700 kbps Bottleneck Bandwidth
1300 kbps Client 2 Bandwidth
Windows 7
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11. MICROSOFT SMOOTH STREAMING
 The MSS client behaves exactly like assumed
 Frequent self caused quality level switching
 Unsmooth playback at the beginning
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12. MPEG-DASH
 Another Verification has been performed with our MPEG-
DASH implementation
 Uses HTTP/1.1 features e.g., persistent connections and pipelining
More efficient than MSS, therefore network conditions has been
modified. Otherwise both clients were able to stream both qualities
smooth in parallel.
700 kbps
Client 2 Bandwidth
Client 1 Bandwidth
1300 kbps
Bottleneck Bandwidth
 The adaptation logic selects individual segments based on
throughput measurements of previous segments
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13. MPEG-DASH
 Same problems like the MSS client
 More frequent quality level switching due to the more aggressive
adaptation
 Lower buffer level and unsmooth playback
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14. FAIR ADAPTATION
 Tries to address this problems and consider the locality of
segments
 MPEG-DASH VLC plug-in has been
extended for Fair Adaptation
 Uses a probe function to verify the
measured throughput
 Non-Cacheable object on the server
 The proxy server could actively modify
the MPD
 The proxy could provide a service
 Client could download the first few bytes
or a random byte range
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15. FAIR ADAPTATION
 Probe in combination with an exponential backoff depicted
with green vertical lines
 No frequent self caused quality switching
 More stable buffer level
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16. FAIR ADAPTATION
 Client problems
 Self caused quality switching has been eliminated
 No rebuffering events or stalls have been occurred
 Increases average buffer fill state
 Increases stability of the session
 Other clients will not be influenced
 Bottleneck performance
 Maximizes the representation reuse
 Minimizes the used bottleneck bandwidth
 Network and Standard
 No changes on the network side are needed
 No changes in the standard are needed
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17. CONCLUSION
 Uncontrolled distribution of content over caching proxies could
negatively influence the streaming performance of several
clients
 Experimentally evaluated the effects of caching proxies on
dynamic adaptive streaming over HTTP
 Assumptions have been proven with Microsoft Smooth Streaming
and MPEG-DASH
 The negative effects depend on the streaming logic and the client
constellation
 A Fair Adaptation Algorithm has been proposed that reduces
the negative effects
 Needs no changes on the standard or network side
 Further work will include the dynamic case and more clients
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18. THANK YOU FOR YOUR ATTENTION
… questions, comments, etc. are welcome …
Christopher Mueller | dash.itec.aau.at
Alpen-Adria Universität Klagenfurt (AAU)  Faculty of Technical Sciences (TEWI)
Institute of Information Technology (ITEC)  Multimedia Communication (MMC)
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19. ALGORITHM IN DETAIL
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