Yao George Mason University Fei George Mason University Lei Microsoft Yang Bell Labs Songqing George Mason University BlueStreaming: Towards Power-Efficient Internet P2P Streaming to Mobile Devices

Internet streaming Internet video streaming is gaining increased popularity in practice – 90% of Internet traffic will be video by 2014 Internet peer-to-peer (P2P) streaming is also popular – P2P TV has generated 6% of total Internet traffic today

Internet streaming to mobile devices Mobile devices are pervasively used today to access streaming services More than 66% of mobile network traffic will be video by 2015

Streaming to mobile devices is challenging Heterogeneity among devices – Software: different mobile operating systems, supported audio/video codecs… – Hardware: different screen sizes… – Connection: 3G, WiFi, WiMAX, … Less reliable wireless connections Slower CPUs … Limited battery power supply Major power drainage sources: – CPU – Display – Wireless network interface card (WNIC) How to save the power consumed by Wireless Network Interface? 30% ~ 40%

Power saving for P2P streaming to mobile devices is even more challenging In addition to downloading, a peer is expected to upload an equivalent amount to other peers in order to get service – Tit-for-tat In order to upload and download, a peer has to frequently exchange control packets with neighbors – Buffermaps – Fine-grained data requests Streaming data is downloaded from multiple and dynamically changing neighbors

Our contribution Through Internet measurements, we confirm the uploading traffic, control traffic significantly prevent the WiFi interface from switching to sleep mode We propose to leverage Bluetooth to transmit highly frequent and low throughput control traffic in P2P streaming for mobile devices We design and implement BlueStreaming, which trades Bluetooths power consumption for greater power saving from WiFi via intelligent traffic shaping

Outline Introduction Internet Measurement Design of BlueStreaming Evaluation Conclusion

P2P streaming consumes more energy than C/S based streaming on iTouch ArchitectureEncoding Rate (Kbps) Sleep Time (%) TVUPlayerP2P28126 Justin.tvC/S28183 iPod Touch Experiments on iPod Touch – Use Pwr Mgt flag to determine the sleep time

P2P streaming consumes more energy than C/S based streaming on laptop ArchitectureEncoding Rate (Kbps) Sleep Time (%) Avg. # of Neighbors PPTVP2P PPSP2P SopCastP2P QQLiveP2P Justin.tvC/S n/a Laptop Windows 7 Experiments on Laptop running Windows 7: – With maximum WiFi Power Saving Enabled

60-75% total transmitted packets are control packets SopCast (530 Kbps)QQLive (500 Kbps) PPTV (400 Kbps) PPS (396 Kbps) Significantly reduces inter-packet delay Results in less sleep time, and more power consumption Smaller than streaming data packets Up to 2 times more than streaming data traffic

SopCast (530 Kbps)QQLive (500 Kbps) Control traffic throughput is low PPTV (400 Kbps) PPS (396 Kbps) Throughput is generally less than 100 Kbps Smaller compared to the streaming rate of Kbps

Uploading traffic varies SopCast (530 Kbps) QQLive (500 Kbps) PPTV (400 Kbps) PPS (396 Kbps) Throughput of uploading traffic varies between 10 Kbps to 1.5 Mbps MAXMIN PPTV4.42%0.08% PPS0.09%0.00% SopCast0.99%0.22% QQLive7.12%4.33%

Summary Control packets are delay-sensitive, highly frequent, but their throughput is low Uploading traffic changes dynamically, and could reach a very high throughput # of neighbors directly affect the control traffic and uploading traffic amount, the response time variance further shortens inter-packet delay

Outline Problem Statement and Proposal Internet Measurement Design of BlueStreaming Evaluation Conclusion

Let the media traffic arrive in a predicable pattern: – Periodic bursts – WiFi can work / sleep correspondingly – Allows the WiFi interface to exploit more sleep opportunities Traffic shaping Time Sleeping Time

How about direct traffic shaping? With traffic shaping: – Control packets, streaming data packets, and uploading packets are scheduled together periodically – Delayed control packets caused: Playback freezing, distortion 10% more streaming packets are received QQLive 500 Kbps Total # of Streaming Packets WiFi Sleep Time (%) Distortion/Freeze Time (%) Adaptive PSM109, WiFi with traffic shaping121, Control traffic is delay-sensitive!! Re-requests

How about using Bluetooth directly? Using Bluetooth to access P2P streaming: – Bluetooth also has lower data rate, and cannot afford the streaming rate – Only 34% streaming data packets were received QQLive 500 Kbps Total # of Streaming Packets WiFi Sleep Time (%) Distortion/Freeze Time (%) Adaptive PSM109, WiFi with traffic shaping121, Bluetooth only37,228n/a96

BlueStreaming overview Traffic Classifier at AP and client: – Decouples control traffic from streaming data traffic, and uses Bluetooth to transmit Traffic Shaper at the client: – Intelligently shapes streaming data downloading traffic, and allows WiFi to save more power Uploading Scheduler at the client: – Handles the uploading traffic with minimized extra power consumption

Decouple control traffic from uploading traffic and streaming data traffic How can control traffic be decoupled from streaming data traffic transparently? Traffic classifier: diverting control traffic to Bluetooth WiFi Time

Control packets are identified empirically based on packet sizes Bluetooth is always on to transmit delay- sensitive control packets Traffic classifier: diverting control traffic to Bluetooth Bluetooth WiFi Time

Buffers streaming data packets at Access Point Applies client-centric traffic shaping, and schedules transmission in a burst periodically How should the burst interval be set? Traffic shaper: shaping ingress streaming traffic intelligently ? Time Bluetooth WiFi Sleeping

How should the burst interval be set? – P2P streaming applications have a re-request timer to determine if a chunk should be re- requested. Application-specific – Packets should be transmitted before re- request timer times out: Traffic shaper: shaping ingress streaming traffic intelligently

How can a client perform uploading with minimized battery power consumption? Priority-based Bluetooth Uploading Uploading scheduler: scheduling uploading wisely Time Bluetooth WiFi Sleeping

How can a client perform uploading with minimized battery power consumption? Opportunistic WiFi Uploading: – Allows WiFi to upload with a minimum consumption of extra battery power – Works seamlessly with the PSM mechanism Uploading scheduler: scheduling uploading wisely Time Bluetooth WiFi Sleeping

Infrastructure Mode A dedicated AP with both WiFi and Bluetooth A BlueStreaming client connects to the AP directly Hybrid Mode WiFi AP does not need to support Bluetooth An intermediate node relays the control traffic to WiFi AP Deployment issue

Outline Problem Statement and Proposal Internet Measurement Design of BlueStreaming Evaluation Conclusion

Implementation of BlueStreaming Prototype systems on Windows and Mac Why laptop instead of mobile devices? – Desktop OS has more complete Bluetooth profiles including Personal Area Network (PAN) – More P2P streaming applications are available on Windows

Experimental setup Use our Windows prototype running on one laptop as BlueStreaming client to access: – PPTV, PPS, SopCast, QQLive Use one MacBook with Bluetooth and WiFi (802.11n at 2.4GHz) as the BlueStreaming Access Point In hybrid mode: – Another laptop is used to relay the control traffic between BlueStreaming client and access point

Infrastructure mode: PPTV results Sleep Time (%)Consumed Energy (J) PSM-A Classifier only PSM-A Classifier only

Infrastructure mode: PPTV results Sleep Time (%)Consumed Energy (J) PSM-A Classifier only BlueStreaming PSM-A Classifier only BlueStreaming

Energy consumption comparisons PPS has very small re-request timeout BlueStreaming effectively saves energy consumption for PPTV, SopCast, QQLive

Conclusion A mobile client in P2P streaming consumes excessive power because of – extra control traffic – extra uploading traffic – dynamics of neighboring peers. BlueStreaming trades Bluetooths power consumption for greater power saving on WiFi interface via intelligent traffic shaping – Saves up to 46% battery power consumption

Thank you!