Bandwidth Consumption Control for Video Streaming

1. Can Basaran ,Kyoung-Don Kang, and Mehmet H. Suzer Department of Computer Science State University of New York Binghamton, USA Bandwidth Consumption Control for Video Streaming

2. Need for Bandwidth Control[Competing Applications] • Excessive, uncontrolled bandwidth consumptions for real-time streaming may starve applications competing for networking medium in a ubiquitous environment • Audio streaming • Web surfing • Instant messaging • File transfer

3. Need for Bandwidth Control[Competing Streams] • A streaming system may have active streams of different priorities • Live streams from the baby room • Streams from security cameras • may have time varying priorities • Movies, sport events… • Available bandwidth should be distributed based on priorities of active streams

4. Need for Bandwidth Control[Mission Critical Systems] • QoS support is even more crucial for mission critical applications • Wireless Sensor Networks • Video streaming • Still images • All can benefit from differentiated services for providing high QoS for hot regions

5. Impact on streams • Large delay and jitter significantly impair user perceived QoS • Important for mission critical applications as well as entertainment systems • Bandwidth limits and priority differentiation should not cause jitter and delay even for the lowest priority streams

6. Provided QoS Support • Control network bandwidth consumptions • Fuzzy control and layered encoding to ensure no more than the specified bandwidth is consumed • Differentiate service to efficiently utilize the limited bandwidth • Prioritization algorithm • The higher the priority, the better the quality • Avoid large delays and jitters via real-time scheduling • Deadlines associated with frames • EDF (earliest deadline first) algorithm

7. Stream behaviour [Why Fuzzy Logic?] • The bandwidth consumption of even a single stream is unpredictable • Hard to come up with a mathematical model • Even the optimal modelwould not be able topredict bursts, resulting in overshoots

8. Scalable Video (SPEG) [Qstream] • Video is encoded in frames of hierarchical layers • Upper enhancement layers can be discarded resulting in a lower quality frame, consuming less bandwidth Base layer Enh. layer 0 Enh. layer 1 Enh. layer 3

9. Prioritization of layers [QStream] • Priorities are assigned to layers based on • the frame type I, P, B • Number of dependent frames • Contribution to overall quality • QStream assigns one of 16 priority levels to each encoding layer, resulting in priority layers

10. Scalable Video [Qstream] • Layers of same priority are grouped together and sent in chunks • To control the bandwidth consumption controller decides on the streaming quality in terms of priority levels

11. Server Structure • Admission Controller accepts or rejects client requests based on base-layer size • Controller • Regulates bandwidth consumption • Gracefully minimizes overshoots • Bursts are handled by the Chopper • Differentiator distributes bandwidth to streams based on their priorities

12. Controller vs. Chopper • Chopper is priority blind • Continuously monitors outgoing traffic and drops packets if it detects an overshoot without looking at which stream they belong to • Can guarantee “no overshoots” • Controller tries to minimize the number of chopper interventions to provide differentiated, smooth streams

13. The Controller • Controller Inputs • Error: e(k) = US - r(k)/RS = 1 - r(k)/RS • Change of error: ∆e(k) = e(k) – e(k-1) • Controller Output: change in quality (∆b(k))

14. The Controller… • Fuzzification: from crisp values to fuzzy linguistic values • Inference: Linguistic output based on table lookup µPS = 1 e(k) = 0.25 ∆ e(k) = 0.0625 µZE = 0.75 µPS = 0.25 µ(PS,PS) = min{1,0.25} = 0.25 µ(PS,ZE) = min{1,0.75} = 0.75 ∆ b(k) ∆ b(k)

15. Network Propagation • In a multi-hop deployment controller signals generated by nodes are propagated to stream sources (servers) • Bottle-neck nodes immediately react via local controller and chopper • Servers adapt to new constraints as they receive control signals from remote clients

16. Network Structure • Propagation of QoS adaptation requests

17. Experiments • 2Mbps bound for video streaming • 4 streams with different priorities • 13 minutes • ~500Kb base layer size • Streams require a total of 8Mbps for full quality • Wired departmental network

18. Total Bandwidth Consumption • 2Mbps bound is not exceeded despite transient bandwidth usage variations due to varying frame sizes • Chopper prevented less than 10 overshoots

19. Service Differentiation • Transient distribution of enhancement layers • Differentiator successfully distributes allocated bandwidth according to priorities Lowest Priority Highest Priority

20. Service Differentiation… • Number of transmitted enhancement layers is not proportional to stream priorities • Controller indirectly controls bandwidth by controlling the stream quality • Sizes of enhancement layers are different • There are limitednumber of enhancement layers

21. Service Differentiation… • Average number of transmitted enhancement layers for different priority streams

22. Video Streaming Quality • Although quality of streams are reduced to fit the allocated bandwidth limit, server can still maintain acceptable quality even for the lowest priority stream

23. Video Streaming Quality…

24. Future Work • Extending SPEG encoding to increase the available priority levels, allowing finer grain control over bandwidth consumption • Adaptive streaming in wireless networks where physical constraints are more strict • Scalable sensor data streaming in wireless sensor networks

25. Questions... Thank You!