Characterizing Netflix Bandwidth Consumption

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Transcription:

Characterizing Netflix Bandwidth Consumption Dr. Jim Martin Associate Professor School of Computing Clemson University jim.martin@cs.clemson.edu http://www.cs.clemson.edu/~jmarty Terry Shaw Director, Network Systems CableLabs t.shaw@cablelabs.com Students: Yunhui Fu (yfu@clemson.edu) Nicholas Wourms (nwourms@clemson.edu) Presented at IEEE CCNC 2013 on January 13, 2013 1

Agenda Background Objectives Methodology Results and Analysis Conclusions Future Work 2

Background 3 Let s rewind a bit: Video streaming over the Internet has evolved from UDPbased streaming, to TCP-based progressive downloading, to adaptive HTTP-based streaming Warning: Different from IPTV!! Several well established methods for adaptive HTTP streaming: Adobe s HTTP Dynamic Streaming (HDS) Apple s HTTP Live Streaming (HLS) Microsoft s Smooth Streaming (SmoothHD) MPEG organization issued a Call for Proposal for an HTTP Streaming Standard (2009). Resulting standard is MPEG-DASH over HTTP and has been published as standard ISO/IEC 23009-1. The 3GPP community has been involved since 2009. 3GP- DASH is in 3GPP standards TS 26.234 and 3GPP TS 26.244.

Background: MPEG DASH A segment is an independent, viewable period of video/audio/timing data. Segment size of 2 seconds or 10 seconds is reasonable. Segments are uniquely identified by an HTTP URL. A client requests the segment, the bit rate, and optionally a specific byte range in the segment. Clients can issue requests and receive segments over any number of concurrent TCP connections. The video segment is sent back by the HTTP server in a burst. The implementation of the client determines how frequently segments are requested, when bit rate adaptation occurs, and the overall sensitivity of the application to network congestion. 4

Throughput (Mbps) Background: DASH Behavior 5 Looking at the first 80 seconds of a Netflix session on a Windows Desktop device. There are multiple startup TCP/HTTP connections that establish the session (Netflix servers) Once the session is established, a CDN server is selected, and this client initiates a single TCP connection to transfer ALL content (video and audio) Trace captured at the client network (all TCP flows captured) We see a high initial throughput as the client fills the playback buffer This is followed by a steady state throughput of 4.39 Mbps Upstream throughput during the 80 seconds was about 1 Kbps. The ratio of downstream traffic to upstream traffic was 3336/1. The ratio of packets sent downstream to upstream was 2.68 70 60 50 40 30 20 10 Buffering state (37.02 Mbps between 10-30 seconds) TCP Cx 1 1.0 second samples 10 second samples Steady state (4.39 Mbps) 0 0 10 20 30 40 50 60 70 80 Time (seconds) a. TCP Throughput of single Cx used for content (Windows device, high speed Internet access (>100Mbps), very good network conditions)

Agenda Background Objectives Methodology Results and Analysis Conclusions Future Work 6

Objectives Characterize the bandwidth consumption and behaviors of an early DASH implementation : Netflix bandwidth consumed, use of multiple TCP connections Explore design/implementation choices: differences across a range of client devices size of playback buffer Netflix Internet Video encoding, Network Congestion Client implementations 7

Agenda Background Objectives Methodology Results and Analysis Conclusions Future Work 8

Methodology Conduct controlled experiments using live Netflix sessions. Analyzed tcpdump packet captures Used four different client devices 9

Methodology: Measurement Scenarios ID Scenario Description 1 Ideal with 3% artificial loss (5 min no impairment, 5 min 3% loss, 5 min no impairment). 2 Ideal with 40% artificial loss (5 min no impairment, 5 min 40 % loss, 5 min no impairment). 3 Stepped loss (200 seconds at 0% loss, 100 seconds at 5% loss, 100 seconds at 10% loss, 100 seconds at 0% loss). 4 Chaotic loss (300 seconds at 0% loss, 300 seconds at variable loss, 300 seconds at 0% loss). 10

Agenda Background Objectives Methodology Results and Analysis Conclusions Future Work 11

Results: Scenario 1 (a) Trace 1-1 (Xbox Wired) (b) Trace 1-5 (Android Wifi)

Results : Scenario 2 13 a. Trace 2-1 (Xbox wired) b. Trace 2-2 (Windows wired)

Agenda Background Objectives Methodology Results and Analysis Conclusions and Future Work 14

Conclusions The basic response to network congestion is similar across the devices that were studied. However, some differences: The steady state bandwidth consumption achieved by different devices during periods of sustained congestion varied. Implementations vary in how aggressive they are to utilize available TCP bandwidth after congestion (and adaptation) has occurred. Use of multiple TCP Connections varies widely across devices. The playback buffer sizes ranged from 30 seconds (on the Android WiFi device) to 4 minutes (on the Windows Wired device). 15

Future Work It is difficult to address the issue of is the adaptation doing the right thing without taking into account perceived video quality. Prior subjective video quality studies suggest that the quality perceived by the end user is assumed better if the rendering uses lower bitrate representations so as to avoid re-buffering stalls and frequent adaptation. Our next step is to validate this conjecture 16

17 Appendix - All Results

Measurement Scenario 1 Results (a) Trace 1-1 (Xbox Wired) (b) Trace 1-2 (Windows Wired) (c) Trace 1-3 (Xbox WiFi) (d) Trace 1-4 (Roku WiFi) (e) Trace 1-5 (Android Wifi)

Measurement Scenario 2 Results (a) Trace 2-1 (Xbox Wired) (b) Trace 2-2 (Windows Wired) (c) Trace 2-3 (Xbox WiFi) (d) Trace 2-4 (Roku WiFi) (e) Trace 2-5 (Android Wifi)

Measurement Scenario 3 Results (a) Trace 3-1 (Xbox Wired) (b) Trace 3-2 (Windows Wired) (c) Trace 3-3 (Xbox WiFi) (d) Trace 3-4 (Roku WiFi)

Measurement Scenario 4 Results (a) Trace 4-1 (Xbox Wired) (b) Trace 4-2 (Windows Wired) (c) Trace 4-3 (Xbox WiFi) (d) Trace 4-4 (Roku WiFi)