Multimedia

1. Multimedia Multimedia on the Internet T.Sharon-A.Frank

2. Is the Internet Real-Time (MM)? T.Sharon-A.Frank

3. Internet Point-to-Point (unicast) Best-Effort Delivery Elastic Applications FIFO Packet Scheduling Provides average Packet Delay End-to-End Reliability Statistical Multiplexing Gain Multimedia Multipoint Soft RT Constraints Inelastic Applications Need Control over Delay and Jitter Various Traffic Classes Need QoS Guarantees Internet/Multimedia Assumptions T.Sharon-A.Frank

4. Application Taxonomy (1) Applications Elastic Inelastic Elastic Applications: Can tolerate relatively large delay variance – essentially the traditional data application. Inelastic Applications: Comparatively intolerant to delay, delay variance, throughput variance and errors. T.Sharon-A.Frank

5. Email: asynchronous message is not real-time delivery in several minutes is acceptable File transfer: interactive service require “quick” transfer “slow” transfer acceptable Network file service: interactive service similar to file transfer fast response required (usually over LAN) WWW: interactive file access mechanism fast response required QoS sensitive content on WWW pages Examples of Elastic Applications T.Sharon-A.Frank

6. Streaming voice: not interactive end-to-end delay not important end-to-end jitter not important data rate and loss very important Real-time voice: person-to-person interactive important to control: end-to-end data rate end-to-end delay end-to-end jitter end-to-end loss Examples of Inelastic Applications T.Sharon-A.Frank

7. Application Taxonomy (2) Applications Elastic Inelastic InteractiveBurst InteractiveBulk AsynchronousBulk Tolerant Intolerant Best EffortLevel 1 Best EffortLevel 2 Best EffortLevel 3 Loose Delay Bounds Firm Delay Bounds TelnetXNFS Web FTP E-MailMM-MailFax Streaming VOD Medical ImagingCAD Schemes T.Sharon-A.Frank

8. QoS Types of Service • Best-effort Service • no/partial guarantees/bounds • Predictive Service • estimation based on past network behavior • Guaranteed Service • deterministic • statistical Current service in most protocols T.Sharon-A.Frank

9. Soft RT QoS Guarantees • Deterministic • Provide Bounds on Performance of all Packets in a Session. • Statistical • No more than a Specified Fraction of Packets will see Performance Below a Certain Specified Value. T.Sharon-A.Frank

10. Deterministic RT QoS Guarantee • Delay: no packets delayed more than D time units on E2E basis (T<=D). • Loss: no packet loss occurs. • Transit Window: bound transit window(Tmax-Tmin<=E). • Queuing: the delay of every packet from session i is less than x at queue j. T.Sharon-A.Frank

11. Statistical RT QoS Guarantee • Delay: no more than x% of packets have a delay larger than D (PR[T>D]<epsilon) • Loss: no more than x% of packets in a session are lost PR[Packet-loss]<epsilon • Queuing: the probability that a packet from session i has a delay greater than x is guaranteed to be less than y at queue j. T.Sharon-A.Frank

12. Application Taxonomy (3) Applications Inelastic Elastic InteractiveBurst InteractiveBulk AsynchronousBulk Tolerant Intolerant Best EffortLevel 1 Best EffortLevel 2 Best EffortLevel 3 Loose Delay Bounds Firm Delay Bounds TelnetXNFS Web FTP E-MailMM-MailFax Streaming VOD Medical ImagingCAD Schemes Best-effort Service Predictive Guaranteed Grab BandwidthNo Certain Arrival TimeUses Data ImmediatelyNo Admission Control The Opposite T.Sharon-A.Frank Care About Average Packet Delay Quantitative Maximum Delay

13. Example: Playback Applications • Audio/Video Services • Soft Real-Time Tolerant Constraints Varying delay transmit sender receiver Network buffer Acquire signal, Digitize, Compress Buffer, Decompress, Playback If arrives late – useless/loss. Playback point: Signal generation time + Fixed offset delay. Compute offset based on max delay: Offset delay can be adjusted • provided by network based on observed delays T.Sharon-A.Frank

14. Internet QoS Models • Adaptation Model • Adapt applications • hide Internet service from the users – scaling • Adapt Internet • Differentiated Services (DiffServ) – simple priority • Extension Model • Integrated Services (IntServ) – resource reservation T.Sharon-A.Frank

15. Adaptation Model • Use network Feedback/Scaling • Adapt applications (Scaling) • Minimal changes to Internet (DiffServ) • No need for Resource Reservation: • “Bandwidth will be infinite”When? Everywhere? Overload? • “Applications can be adaptive”Too slow? Can users adapt? • “Simple priority is sufficient”All high priority? Overload? T.Sharon-A.Frank

16. Scaling Means to sub-sample a data streamand only present a fraction of its original content.Scaling types: • Transparent Scaling - usually by dropping some portion of the data stream. • Non-transparent Scaling - usually by adjusting parameters in the coding algorithm. T.Sharon-A.Frank

17. Scaling in Audio and Video • Audio • Transparent scaling is difficult because human ear is sensitive • usually done by changing sampling rate • Video • Temporal scaling (drop frames) • Spatial scaling (reduce resolution) • Frequency scaling (reduce number of DCT coefficients) • Amplitude scaling (reduce color depth) • Color space scaling (reduce number of color entries or even switch to gray scale) T.Sharon-A.Frank

18. Audio Scaling T.Sharon-A.Frank

19. Scaling Example: Videoconferencing T.Sharon-A.Frank

20. Scaling Example:Videoconferencing (2) T.Sharon-A.Frank

21. Stream Management • Managing streams is all about managing bandwidth, buffers, processing capacity and scheduling priorities – which are all needed in order to realize QoS guarantees. • This is not as simple as it sounds, and there’s no general agreement as to “how” it should be done. • For instance: ATM’s QoS (which is very “rich”) has proven to be unworkable (difficult to implement). • Another technique is the Internet’s RSVP. T.Sharon-A.Frank

22. Improving QoS in IP Networks • IETF groups are working on proposals to provide better QoS control in IP networks, i.e., going beyond best effort to provide some assurance for QoS. • Work in Progress includes Differentiated Services (DiffServ), RSVP and Integrated Services (IntServ). T.Sharon-A.Frank

23. Differentiated Services (DiffServ) • Relatively simple, coarse-grained QoS mechanism. • Deployed in networks without needing to change the operation of the end system application. • Based around marking packets with a small-fixed bit-pattern, which maps to certain handling and forwarding criteria at each hop. T.Sharon-A.Frank

24. Extension Model Need New Integrated Services (IntServ) Model? • Single Service Model • Best-effort services • Soft real-time services • Keep Internet Philosophy • Downward compatible • Common infrastructure • Unified protocol stack • Open/public access • User usage-based pricing T.Sharon-A.Frank

25. Resource Reservation • Pre-allocation of needed resources to guarantee deterministic QoS. • Allocated resources are dedicated; if not used – remain idle. • Example: Internet RSVP – Resource reSerVation Protocol. • If resources cannot be reserved, scaling can be used. T.Sharon-A.Frank

26. Internet RSVP QoS The basic organization of RSVP for resource reservation in a distributed system – transport-level control protocol for enabling resource reservations in routers. Interesting characteristic: receiver initiated. T.Sharon-A.Frank

27. Specifying QoS with Flow Specifications A flow specification – one way of specifying QoS – a little complex, but it does work (but not via a user controlled interface). T.Sharon-A.Frank

28. An Approach to Implementing QoS The principle of a token bucket algorithm – a “classic” technique for controlling the flow of data (and implementing QoS characteristics). T.Sharon-A.Frank

29. Integrated Services (IntServ) • An architecture for providing QOS guarantees in IP networks for individual application sessions. • Relies on resource reservation. • Routers need to maintain state info, maintaining records of allocated resources and responding to new Call setup requests on that basis. T.Sharon-A.Frank