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QoS-Based Multicast Routing for Distributing Layered Video to Heterogeneous Receivers in Rate-based Networks. Bin Wang and Jennifer C.Hou. Goal: QoS requirements of heterogeneous receivers, including bandwidth and delay; Highest receiving quality for receivers

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QoS-Based Multicast Routing for Distributing Layered Video to Heterogeneous Receivers in Rate-based Networks

Bin Wang and Jennifer C.Hou


Goal: to Heterogeneous Receivers in Rate-based Networks

  • QoS requirements of heterogeneous receivers, including bandwidth and delay;

  • Highest receiving quality for receivers

  • Minimize the total network resource consumption

    Solution:

  • Source:Layered encoding(cummulative)

  • Receivers: tradeoff between video quality and available bandwidth

  • Scheduling: rate-based link scheduling

  • Tree construction on weighted digraph G=(V,E) using the global state and an auxiliary routing table


Global state
Global state to Heterogeneous Receivers in Rate-based Networks

Link state:

  • Available bandwidth: b(l), b:ER+,the link bandwidth function,

  • Constant delay: dl,which depends on the capacity,the propagation delay, and the maximum packet size

  • Link cost

    Node state: available buffer…

    Global state:

  • The collection of the local node/link state of all the nodes in the network

  • Maintained by every node in the network


The auxiliary routing table
The Auxiliary Routing Table to Heterogeneous Receivers in Rate-based Networks

T is a |V| X H matrix, recording a h-hop maximum bandwidth path :

  • P: path

  • bw:maximum bandwidth on P

  • Neighbour:next hop

  • dh=sum(dl): end-end constant delay

    *every node maintains a T


Rate based scheduling algorithms
Rate-based Scheduling Algorithms to Heterogeneous Receivers in Rate-based Networks

  • Algorithms: Generalized Processor Sharing,Weighted Fair Queuing,Virtual Clock…

  • Traffic model: leaky bucket (R,sigma)

  • End-end delay bound on P:

    D(r,P)=(sigma+|P|*c)/r+sum(dl)


Traffic model for layered video
Traffic Model for Layered Video to Heterogeneous Receivers in Rate-based Networks

  • Each layer: leaky bucket(R,Sigma)

  • Video signal: (Ri,sigmai), i:1~m (#of layers)

  • Layer k: (Rk,sigmak),

    Rk=sumj=1k(Rj)

    sigmak=sumj=1k(sigmaj)

  • Layers are selectively forwarded on links


Problem formulation
Problem Formulation to Heterogeneous Receivers in Rate-based Networks

The one-to-many multicast video distribution session:

s:source

d={j|j=1~n}: receivers

{Dj|j=1~n}:delay requirements

{Rjr|j=1~n}:maximum acceptable rates, layer-k receiver j: Rk<=Rjr<Rk+1

How to construct a tree?


Algorithm overview
Algorithm Overview to Heterogeneous Receivers in Rate-based Networks

  • Starting from a tree with only s

  • Higher-layer receiver i first

  • Select the most appropriate path P from T

  • A setup message is sent to i along P, carrying the data structure RECEIVER and D(delay)

  • RECEIVER is updated by intermediate nodes, if better path is available

  • Next off-tree receiver j is selected by i

  • A fork message is sent from i

  • A finish message is sent to s if no off-tree node


The recevier data structure
The RECEVIER data structure to Heterogeneous Receivers in Rate-based Networks

RECEIVER.RECEIVER[i] records the least-hop appropriate path P for receiver i:

  • OnTreeNode: initialized to s

  • path: P, with sufficient bandwidth

  • r: the minimum bandwidth ri for delay

  • cost: |P|*r, the total bandwidth due to receiver i(only for new branch)

  • Rr: maximum acceptable rate Rri

  • level: # of layers

  • tag: on-tree or off-tree


Path selection from t
Path Selection from T to Heterogeneous Receivers in Rate-based Networks

  • Calculate the minimum bandwidth ri according to deley requirement:

    ri>=(sigmak+|p|*c)/(Di-sum(dl))

  • Select the least-hop path with T(i,h).bw>=max(ri,Rk)

  • No loop

  • Reserved bandwidth: max(ri,Rk)

  • if no path exists,or ri>Rri, degrading layer

    (Lower cost? Best path?)


Next off tree receiver selection
Next Off-Tree Receiver Selection to Heterogeneous Receivers in Rate-based Networks

Higher layer & Smaller cost node first:

  • Gk+1=…=Gm=0, Gk<>0

  • Select the receiver i from Gk with min(|P|*ri)

  • RECEIVER[i].tag=true

  • A setup message is sent to i

  • i will select next receiver j

  • i sends a fork message to RECEIVER[j].OnTreeNode


Path update
Path Update to Heterogeneous Receivers in Rate-based Networks

Intermediate nodes update D&RECEIVER:

  • Delay requirement (D:cumulative delay) Di>=D+(sigmak+|p|*c)/ri+sum(dl)

  • Select the minimum-hop path P from T(first entry T(i,h))

  • Smaller cost(total bandwidth): |P|*ri

  • Update RECEIVER for every receiver i if smaller cost


Dynamic receiver join leave
Dynamic Receiver Join/Leave to Heterogeneous Receivers in Rate-based Networks

Goal: seamless transition via incremental changing

Leave:

  • Leaf node: leave message is sent upstream,and resource is released by a fork node

  • Non-leaf node: just relay incoming downstream messages


Dynamic receiver join leave cond
Dynamic Receiver Join/Leave(cond.) to Heterogeneous Receivers in Rate-based Networks

Join:

  • Join request to s with di&Rir

  • S multicasts a join message with RECEIVER[i]&D to all(?) on-tree receivers

  • Intermediate nodes updates D,and RECEIVER if smaller cost path available

  • The leaf receivers send back RECEIVER

  • S select a fork node with least cost

  • fork message

    (Why not use updated T? Least cost?)


Auxiliary routing table t update
Auxiliary Routing Table T Update to Heterogeneous Receivers in Rate-based Networks

Compute the h-hop maximum bandwidth paths from the current node to all the other nodes:iterate H times, h=1~H

  • Update T(j,h)(j=1~|V): for every neighbour u of j, if no loop

    T(j,h).bw=max(T(j,h).bw,min(T(u,h-1).bw,b(u,j)))

  • If loop exists(j in T(u,h-1).P), recursively calculate a new T(u,h-1) excluding j

  • For complexity, excluding u if loop or limit the scope of recursion

  • Run off-line and infrequently


Complexity
Complexity to Heterogeneous Receivers in Rate-based Networks

  • # of messages: O(2*|d|)

  • T update: exponential in the worst case

    If bapassing the loop:

    Check every neighbour u of j: O(|V|)

    Check loop and bw: O(H)+1

    Run H times for every receiver:

    O(H)*O(|V|)

    So O(H2*|V|2)


Simulation
Simulation to Heterogeneous Receivers in Rate-based Networks

  • Topology:

    vBNS , switch cluster,random network(Waxman method, which can obtain “real world” networks)

  • Simulator: NetSimQ

  • Comparing:

    maximum bandwidth tree algorithm

    Maxemchuk’s algorithm

  • Varing parameters: lambda(session arrival rate),|d|,Dj

  • Performance metrics: total bandwidth required, percentage of receivers attaining QoS


Maxemchuk s algorithm
Maxemchuk’s Algorithm to Heterogeneous Receivers in Rate-based Networks

  • Minimize bandwidth consumption without considering QoS requirement

  • Use modified T-M heuristic

  • A variant of steiner tree problem: construct a minimum cost tree for a subset of nodes,

    with link cost fixed in the network

  • Link cost: basic cost *highest reserved rate

  • Construct from higher-rate receivers and then add lower-rate of receivers

  • No explicit QoS consideration

  • Centralization


Max bandwidth tree algorithm
Max Bandwidth Tree Algorithm to Heterogeneous Receivers in Rate-based Networks

  • For Layered-encoded data (cumulative)

  • Compute the maximum available bandwidth tree to connect all receivers,receivers are classified by receiving capabilities

  • Minimize the sum of satisfaction level

  • For shorter path:select the node nearest to source (not guarantee shortest path)

  • For bandwidth saving: reduce bandwidth from the receivers


Simulation results
Simulation results to Heterogeneous Receivers in Rate-based Networks


Simulation results cond
Simulation results(cond) to Heterogeneous Receivers in Rate-based Networks


Simulation results cond1
Simulation results(cond) to Heterogeneous Receivers in Rate-based Networks


Simulation results cond2
Simulation results(cond) to Heterogeneous Receivers in Rate-based Networks


Issues
Issues: to Heterogeneous Receivers in Rate-based Networks

  • The original Goal is achieved

  • Shortest path? Smallest total cost?The best path?

  • Complexity (scalability?):

    Global state

    T update

    Link state update

    Complexity!

  • A good attemption!


A Better Solution? to Heterogeneous Receivers in Rate-based Networks


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