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Multipath Routing for Video Delivery over Bandwidth-Limited Networks. S.-H. Gary Chan Jiancong Chen Department of Computer Science Hong Kong University of Science and Technology Clear Water Bay, Kowloon. Outline. Introduction

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Multipath Routing for Video Delivery over Bandwidth-Limited Networks


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multipath routing for video delivery over bandwidth limited networks

Multipath Routing for Video Delivery over Bandwidth-Limited Networks

S.-H. Gary Chan Jiancong Chen

Department of Computer Science

Hong Kong University of Science and Technology

Clear Water Bay, Kowloon

outline
Outline

Introduction

Multipath routing heuristic for point-to-point video delivery

Scheduling algorithm at the server to achieve the theoretical minimum start-up delay

Extension to point-to-multipoint layered video delivery

Conclusion

research motivation
Research Motivation
  • Deliver quality video services over bandwidth-limited networks (e.g., the Internet)
  • Video application requirements
    • High bandwidth
    • Low start-up delay or network transmission cost
  • Traditional routing based on single path approach (e.g., the shortest path routing) is no longer sufficient to meet the bandwidth requirement
    • QoS routing
negotiating and guaranteeing qos in the internet
Negotiating and Guaranteeing QoS in the Internet
  • Integrated services/Resource Reservation Protocol (RSVP)
  • Multi-protocol label switching (MPLS)
  • Differentiated services model (DiffServ)
  • Traffic engineering
  • Constraint-based routing
constraint based routing
Constraint-Based Routing
  • Compute routes subject to multiple constraints
    • Distribution of link state information
    • Route computation
  • Goals
    • Select routes that can meet certain QoS requirements
    • Increase utilization of the network
meeting bandwidth requirement with low delay multipath routing
Meeting Bandwidth Requirement with Low Delay: Multipath Routing
  • The video data is transmitted over multiple paths in the network
    • Increasing the overall aggregate delivery bandwidth
    • Routing to meet the bandwidth requirement
  • The end host needs to do reassembly
    • Increasing the start up delay
    • Server scheduling to reduce the delay
previous work on multipath routing
Previous Work on Multipath Routing
  • Search multiple paths and select the best one
    • E.g., selective probing
  • Find multiple paths for a connection (e.g., disjoint paths routing)
    • Mainly designed for reliability rather than high aggregate bandwidth
our work
Our Work
  • A multipath heuristics for point-to-point video delivery
    • Low delay and buffer requirement
    • Efficient
  • Given a set of path lengths
    • The theoretical minimum delay achievable
    • A scheduling algorithm to achieve that
  • For point-to-multipoint communication with heterogeneous bandwidth requirement
    • How the multicast trees should be constructed to minimize the cost of the tree-aggregate
    • The corresponding number and bandwidth of the video layers
multipath problem formulation bandwidth constrained delay optimized problem
Multipath Problem Formulation: Bandwidth-Constrained Delay-Optimized Problem
  • Given:
    • A source s
    • A destination t
    • Bandwidth requirement B
      • B less than the max-flow of the network
  • Find routing and scheduling algorithms to achieve
    • Bandwidth no less than B
    • Minimum delay
desirable properties of routing algorithms
Desirable Properties of Routing Algorithms
  • Efficient
    • Similar complexity as the shortest path routing
    • Fast route convergence
  • Achieving high end-to-end bandwidth
    • Preferably the max-flow of the network
  • Amendable to the current Internet routing
a multipath routing heuristics
A Multipath Routing Heuristics
  • Find the max-flow sub-graph G’ of the network
  • Find the shortest-path in the sub-graph G’
  • If the aggregated bandwidth of the path(s) found is sufficient, return
  • Subtract the bandwidth from G’ along the path just found
  • Repeat steps 2 to 4
an example

(20,7)

(20,7)

v1

v1

v4

v4

(10,12)

(10,12)

(8,13)

(8,13)

(15,6)

(15,6)

(5,13)

s

s

v3

v3

t

t

(10,5)

(10,5)

(10,10)

(15,7)

(15,7)

(10,8)

(10,8)

(15,7)

(15,7)

(20,6)

(20,6)

v2

v2

v5

v5

(10,14)

An Example
simulation model
Simulation Model
  • Hierarchical network
    • 3-hierarchy nodes: backbone routers, border routers and intra-domain routers
    • Random links
  • System parameters
    • Network size
    • Network density
    • Connectivity, etc
comparison with the traditional approaches
Comparison with the Traditional Approaches
  • Shortest path
  • Shortest-feasible path
    • Remove the links with insufficient bandwidth
    • Run the shortest path algorithm over the residual network
  • Performance measures
    • Success rate in meeting the bandwidth requirement
    • Bandwidth achieved
    • End-to-end delay, given by the longest path
hierarchical routing
Hierarchical routing
  • Logical hierarchical topology as in the Internet
  • State information
    • Only full local information is maintained
    • Remote state information is partially maintained
  • Compute multiple routes in the regions in parallel
    • Reduce computation complexity, processing time, and storage
an example22

s

t

An example

Upper hierarchy

Lower hierarchy

problem formulation
Problem Formulation
  • Given a set of path lengths
  • What is the theoretical minimum start-up delay achievable if video data can be scheduled?
    • Guarantee continuity
  • Find a data scheduling algorithm at the server to achieve such minimum delay
    • No other algorithms can achieve lower delay while maintaining stream continuity
a simple case
A Simple Case
  • Two paths with the same bandwidth of B/2 but different delays d1and d2 (d1< d2)
  • Without server scheduling, the start-up delay equals the delay of the longer path, i.e., d2
the theoretical minimum delay

Data

Slope=B

Slope=B/2

Time

d2

d1

0

original delay

minimized delay

The Theoretical Minimum Delay
  • Data production and consumption curves
    • The difference is the buffer requirement
  • In the example, the minimum start-up delay is (d1+d2)/2
the idea
The Idea
  • Don’t indiscriminately multiplex video packets along all the paths
  • The server sends the video prefixes along the shorter paths
  • The client plays back the prefixes with stream continuity
    • Before the data from the longest path arrives
the scheduling algorithm

Video data

To path 1

To path 2

To path 1

The Scheduling Algorithm
  • The video sequence is partitioned into segments
  • All the segments are transmitted in parallel over the multiple paths
  • The earlier segments are transmitted over the shorter paths
general case of scheduling
General Case of Scheduling

p

K

p

2

p

3

.

.

.

p

.

.

.

1

p

p

2

1

p

2

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1

1

.

.

.

t

t

t

t

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2

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an exact solution solving the multipath problem
An Exact Solution Solving the Multipath Problem
  • A network with unit link bandwidth
  • Multipath is disjoint paths
  • With scheduling, the problem is to find the shortest-disjoint paths (SDP)
    • Bandwidth requirement: B units
    • Find the B-shortest-disjoint paths
      • The sum of their delays is minimum
    • The shortest-disjoint paths algorithm is well known
a video multicast system
A Video Multicast System
  • A server and multiple clients
    • The clients have different bandwidth requirements
    • A link is characterized by its bandwidth and cost
  • Find multiple multicast trees spanning the multicast group
    • Meeting the heterogeneous bandwidth requirements of the members
    • With minimum cost of the tree-aggregate
  • Assignment of video layers
    • A base layer and several enhancement layers
    • The number of video layers, and
    • Their respective bandwidths
a simple case34
A Simple Case
  • All the users have the same requirement B
  • Multiple trees are used to span all the users
    • With minimum cost of the tree-aggregate
  • If all the bandwidth requirements are met
    • A single video layer with bandwidth B
  • Otherwise, layered video can be used
    • The higher layers serve users with increasing end-to-end bandwidth
an example35

Users

Base layer tree 1

Base layer tree 2

Enh. layer tree 1

An Example

s

problem formulation bandwidth constrained cost optimized problem
Problem Formulation: Bandwidth-Constrained Cost-Optimized Problem
  • Given
    • A source s
    • A set of destinations Y (= {y1, y2,…, yn})
    • Bandwidth requirement B (= {b1, b2,…, bn} )
  • Find multiple trees T to achieve
    • Bandwidth no less than bifor yi
    • Minimum cost of the aggregated “mesh”
  • The corresponding number and bandwidth of the layers, and along which trees a layer transmits
  • Multiple trees
    • To find a min-cost tree (Steiner tree) is NP-hard
    • To construct such multiple trees is even harder
two heuristics multipath extension
Two Heuristics: Multipath Extension
  • Based on point-to-point multipath heuristic
  • First meet the bandwidth requirement of each user with the multipath heuristics
  • Aggregate the paths
  • Construct trees out of the paths-aggregate
    • Each tree has a certain bandwidth equal to the bandwidth of the bottleneck link
    • There is at least one tree spanning all the users
  • Complexity: O(m|V|3)
  • Bandwidth-first approach
min cost tree extension
Min-Cost Tree Extension
  • First find a min-cost multicast tree spanning all the users
  • Add branches to the tree until all the bandwidth requirements are met
    • Closest receivers
    • Forming new trees
  • Complexity: O(mB|V|2)
  • Cost-first approach
bandwidth assignment of layers
Bandwidth Assignment of Layers
  • Group the trees spanning the same set of users
  • Arrange these groups according to decreasing number of users covered
    • The previous set of users is the superset of the latter
  • The aggregate bandwidth of the first tree-group is the bandwidth of the base layer
  • The aggregate bandwidth of the 2nd group is the bandwidth of the enhancement layer 1, and so on
an example on layering

Users

Base layer tree 1

Base layer tree 2

Enh. layer tree 1

An Example on Layering

s

simulation results
Simulation Results
  • Hierarchical network
  • Comparing with a single-tree approach (shortest path tree)
  • Performance measures
    • Success rate of meeting the bandwidth requirements of the users
    • Average bandwidth achieved
    • Cost
conclusion
Conclusion
  • Video routing over a bandwidth-limited network
  • Multi-path heuristic
    • Achieve high end-to-end bandwidth with low delay
  • Video scheduling algorithm at the server
    • Reduce the start-up delay to the theoretical minimum
  • Extension to multicast environment
    • Meeting heterogeneous bandwidth requirements
    • Minimum cost of the tree-aggregate