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AGENDA
� Overview
� Video streaming over UMTS
� UMTS Enhancement: HSDPA
� Scalable Video Codec
� State of the Art
� Open Issues
� Possible Approaches
Streaming of Scalable Video over
UMTS
UMTS
Core
Network
UMTS
Core
Network
Feedback
Node B
RNC
Video server in
Internet
Video
Client
UMTS
network
Streaming of Scalable Video over
UMTS …
� Focus on the last link (UMTS): Bottleneck� Scarce & Variable Bandwidth
� Wireless Losses
� Internet is initially assumed to be ideal
� Use of Recent Video Codecs
Streaming of Scalable Video over
UMTS …
� Scalable Video Codec (MPEG-4 SVC)
� Flexible Bit-Rate adaptation with graceful change in Quality
Video Data
Increasing Bit-Rate
Decreasing Quality
AGENDA
� Overview
� State of the Art
� QoS in wired networks: Diffserv
� Streaming of MPEG-2 & H.264
� Open Issues
� Possible Approaches
State of the Art: QoS in the Wired network
� IETF has defined an architecture for differential service (DIFFSERV)
� Diffserv Per-Hop-Behaviors:
� Best Effort: Current Internet
� Expedited Forwarding: Topmost priority
� Assured Forwarding: Classification & Discard probabilities
� Packets are marked: Green, Yellow, Red
� Green packets are given most priority and Red packets are given the least priority
State of the Art: Video Codecs
� MPEG-2 & H.264� Constant Bit-Rate
� Some packets are more important than the others
� I, P and B frames: � I frames are the most important and B frames are the least important
� Simple Diffserv-aware marking
� I � Green; P � Yellow; B �Red
� Drop Red packets on Congestion & Protect Green packets
AGENDA
� Overview
� State of the Art
� Open Issues
� QoS in UMTS
� Congestion Control
� Scalable Video Codec
� Possible Approaches
Open Issues : In General
� UMTS Network� Is different from Wired Network
� Variable Bandwidth
� Scarce Bandwidth� Users should use congestion control
� Wireless Losses
� How to do Congestion control for Video?� When many users share the same resources
� How to provide QoS in UMTS?
Open Issues : In General …
� Scalable Video Codec (MPEG-4 SVC)
� How to do QoS/Diffserv mapping (coloring)?
� No straight-forward mapping like : I � Green; P � Yellow; B �Red
Open Issues : General Picture
UMTS
Network
UMTS
Network
Feedback
Node B
RNC
How to color packets for almost ideally scalable
Video?
How to provide end to end congestion control for video
streaming over networks like UMTS?
How to Provide QoS in
UMTS network?
Video server
In Context of Different Layers
� IP LAYER:
� To provide QoS in UMTS network
� TRANSPORT LAYER:
� Congestion control over UMTS network
� APPLICATION LAYER:
� QoS/Diffserv coloring of scalable video
IP LAYER
� Quality of Service (QoS) : Basics� Priority to important traffic
� Differentiation of service
� Limiting traffic through Service Level Agreements (SLAs)
� Hard bit-rate constraints � User A will not transmit more than 100kbps of green packets
� Soft constraints through Pricing� Green packets will cost c cents per kilobytes
� Guarantees of bit-rate, delay, losses
IP LAYER …(Impact of MAC layer)
� QoS in UMTS: Impact of Packet Scheduling strategies
User 1
User 2
Node B
Channel Quality feedback
MAX C/I Scheduler gives the channel to best user
IP LAYER …(Impact of MAC layer)
� QoS in UMTS: Impact of Packet Scheduling strategies…
Increased fairness among users
Increased Cell Capacity
Fair throughput scheduling
Proportional Fair scheduling
Max C/I scheduling
IP LAYER …
� QoS in UMTS: Problems and Solutions
� How to implement 4 QoS classes of UMTS?
� How to use the available schedulers?
� Variable Bandwidth
� Problems:� Difficult to implement Hard bit-rate constraints
� Difficult to give guarantees for bit-rates
� Solutions� Soft constraints like Pricing are possible
� Dynamic SLAs
Work in Progress
IP LAYER …
� QoS through Buffer Management
� RED (Random Early Detection)
� Proactive Dropping: Doesn’t wait for buffer to become full
� Controls Delay: Stabilizes the queue length to a target value
IP LAYER …
� QoS through Buffer Management …
� RIO (RED In and Out) for Diffserv
� Differential dropping (Green, Yellow & Red)
IP LAYER …
� QoS through Buffer Management …
� Problems:
� Strategies like RED will not be efficient
� Per user queues (unlike wired network)
� Variable Link Bandwidth creates problem in setting RED parameters
� No use in stabilizing “queue length (q)” because Bandwidth is variable
IP LAYER …
� QoS through Buffer Management …
� Solutions: Per user queues make things easier
� Each Queue will hold only Few flows (1 flow..)
� ECN (Explicit congestion Notification) can be used.
� To notify end users to reduce their rate
� Users will not be able to cheat because of per user queues
� Adapting RED to variable bandwidth using control theory
� A new buffer management scheme adapted to UMTS
Work in Progress
Work in Progress
TRANSPORT LAYER
� Congestion Control� Confusion between Congestion and wireless losses
� WLED (Wireless loss estimation in Diffserv networks)
� Green packets will not be dropped during congestion
� Wireless losses and green losses will be correlated
� ECN can be used to differentiate losses
� Congestion control for Video
� TCP
� TFRC
� KELLY Control
Done
TRANSPORT LAYER …
� TCP� Many things to learn from TCP
� Current stability of internet is due to TCP
� Good approach for tackling congestion
� Not suitable for Video transmission � “Some” retransmissions are a waste
� Video can tolerate errors
� Oscillation in throughput is undesirable for Video transmission
TRANSPORT LAYER …
� TFRC (TCP Friendly Rate control)
� TCP Friendly as it tries to imitate TCP in a smooth way
� Rate is based on an equation:
� Receiver sends feedback at least once per RTT
� Feedback can contain loss event rate or the Rate itself
TRANSPORT LAYER …
� TFRC …� TFRC with UMTS/HSDPA
� High Jitter � causes NO-ACK timeouts
� TFRC decreases its throughput
� RTT estimation not optimal
� Do a simulation study of TFRC using EURANE platform (UMTS-HSDPA)
� Some TCP strategies that solve jitter issues can be tested with TFRC
� NO-ACK timer can be increased
� RTT estimation can be modified
� Reduce Jitter through buffer management
Work in Progress
TRANSPORT LAYER …
� Kelly Control� The idea is to model end-users as an optimization, game theoretic problem
� Assume each user i derives utility Ui(xi) from the network by obtaining throughput xi
� User’s Game
� Assume that each user is willing to pay price wi for using the network and that it receives throughput proportional to wi: xi = wi / λi
(λi is charge per unit flow for user i)
� Max [Ui(wi / λi) - wi]
� Network’s Game
� Max ∑wilogxi subject to ∑ Rij xi ≤ Cj , i, j
TRANSPORT LAYER …
� Kelly Control …� Network is not a centralized entity, so a solution in a distributed fashion
� This can be achieved by the end user equations:
dxi(t) / dt = k(wi – xi(t) ∑ Rijpj(t) )� Where k > 0 is a constant and pj is the price charged by the router j for using its resources
pj(t) = pj(∑ Rkjxk(t))� In real network we can replace price with packet loss feedback
APPLICATION LAYER
How to color the packets and how to represent the
Video?
� Packet Coloring Problem
APPLICATION LAYER …
� Scalable Video Representation [Chou01]
� Divided Video into data units connected by an Acyclic graph
� Rate-Distortion Optimized streaming
APPLICATION LAYER …
� A new transport protocol can be designed
� Selectively retransmits the data depending on its importance
� Receiver has a Play out buffer of 1 to 8 seconds
� Important packets can be retransmitted
APPLICATION LAYER …
� Packet coloring approaches
� Cost-Quality Optimization
� Consider “green” channel as costly but more reliable
� Consider “red” channel as cheap but lossy
� Optimize streaming between these channels
� Other approaches
� Let red packets bear the rate fluctuations and Protect green packets from congestion