Transcript mm9-2_qos
Multimedia Multimedia on the Internet 1 T.Sharon-A.Frank Is the Internet Real-Time (MM)? 2 T.Sharon-A.Frank Internet/Multimedia Assumptions • Internet • Multimedia – – – – – Point-to-Point (unicast) Best-Effort Delivery Elastic Applications FIFO Packet Scheduling Provides average Packet Delay – End-to-End Reliability – Statistical Multiplexing Gain 3 T.Sharon-A.Frank – – – – Multipoint Soft RT Constraints Inelastic Applications Need Control over Delay and Jitter – Various Traffic Classes – Need QoS Guarantees Application Taxonomy (1) Applications Elastic Inelastic Elastic Applications: Can tolerate relatively large delay variance – essentially the traditional data application. 4 T.Sharon-A.Frank Inelastic Applications: Comparatively intolerant to delay, delay variance, throughput variance and errors. Examples of Elastic Applications • Network file service: • Email: – asynchronous – message is not real-time – delivery in several minutes is acceptable • File transfer: – interactive service – require “quick” transfer – “slow” transfer acceptable 5 T.Sharon-A.Frank – – – – 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 Inelastic Applications • Real-time voice: • Streaming voice: – not interactive – end-to-end delay not important – end-to-end jitter not important – data rate and loss very important 6 – person-to-person – interactive – important to control: • end-to-end data rate • end-to-end delay • end-to-end jitter • end-to-end loss T.Sharon-A.Frank Application Taxonomy (2) Applications Elastic Inelastic Interactive Interactive Asynchronous Burst Bulk Bulk Best Effort Level 1 Telnet X NFS Web 7 Best Effort Level 2 FTP Tolerant Intolerant Best Effort Level 3 Loose Delay Bounds Firm Delay Bounds E-Mail MM-Mail Fax Streamin g VOD Medical Imaging CAD Schemes T.Sharon-A.Frank QoS Types of Service Best-effort Service no/partial guarantees/bounds Predictive Service estimation based on past network behavior Guaranteed Service deterministic statistical 8 T.Sharon-A.Frank 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. 9 T.Sharon-A.Frank 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. 10 T.Sharon-A.Frank 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. 11 T.Sharon-A.Frank Application Taxonomy (3) Applications Inelastic Elastic Interactive Interactive Asynchronous Burst Bulk Bulk Best Effort Level 1 Telnet X NFS Web 12 Best Effort Level 2 FTP Tolerant Intolerant Best Effort Level 3 Loose Delay Bounds Firm Delay Bounds E-Mail MM-Mail Fax Streamin g VOD Medical Imaging CAD Schemes Best-effort Service Grab Bandwidth No Certain Arrival Time Uses Data Immediately No Admission Control Predictive Guaranteed The Opposite T.Sharon-A.Frank Care About Average Packet Delay Quantitative Maximum Delay Example: Playback Applications • Audio/Video Services • Soft Real-Time Tolerant Constraints sender Varying delay transmit receiver Network buffer Acquire signal, Digitize, Compress 13 Buffer, Decompress, Playback If arrives late – useless/loss. Playback point: Signal generation time + Fixed offset delay. Compute offset based on max delay: provided by network based on observed Offset delay can be adjusted T.Sharon-A.Frank delays 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 14 T.Sharon-A.Frank 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? 15 T.Sharon-A.Frank Scaling Means to sub-sample a data stream and only present a fraction of its original content. Scaling types: Transparent Scaling usually by dropping some portion of the data stream. Non-transparent Scaling 16 usually by adjusting parameters in the coding algorithm. T.Sharon-A.Frank Scaling in Audio and Video Audio – Transparent scaling is difficult because human ear is sensitive – usually done by changing sampling rate Video – – – – – 17 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 Audio Scaling 18 T.Sharon-A.Frank Scaling Example: Videoconferencing 19 T.Sharon-A.Frank Scaling Example:Videoconferencing (2) 20 T.Sharon-A.Frank 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. 21 T.Sharon-A.Frank 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). 22 T.Sharon-A.Frank 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 smallfixed bit-pattern, which maps to certain handling and forwarding criteria at each hop. 23 T.Sharon-A.Frank Extension Model Need New Integrated Services (IntServ) Model? • Single Service Model – Best-effort services – Soft real-time services • Keep Internet Philosophy – – – – – 24 Downward compatible Common infrastructure Unified protocol stack Open/public access User usage-based pricing T.Sharon-A.Frank 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. 25 T.Sharon-A.Frank 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. 26 T.Sharon-A.Frank Specifying QoS with Flow Specifications 27 Characteristics of the Input Service Required • maximum data unit size (bytes) • Token bucket rate (bytes/sec) • Toke bucket size (bytes) • Maximum transmission rate (bytes/sec) • • • • • • Loss sensitivity (bytes) Loss interval (sec) Burst loss sensitivity (data units) Minimum delay noticed (sec) Maximum delay variation (sec) Quality of guarantee 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 An Approach to Implementing QoS 28 The principle of a token bucket algorithm – a “classic” technique for controlling the flow of data (and implementing QoS characteristics). T.Sharon-A.Frank 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. 29 T.Sharon-A.Frank