Video Streaming over DiffServ and some other Issues

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Video Streaming over DiffServ and some other
Issues

• Presented by Wei Wei

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Outline

• A framework for video streaming over DiffServ
  network
• A novel node mechanism for video streaming over
  DiffServ network
• A case study for aggregation and conformance in
  DiffServ network
• Pricing, Provisioning and Peering of DiffServ
  network

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Framework for Video over DiffServ1

• This paper presents a framework for
  quality-of-service mapping between categorized
  packet video and relative DiffServ network.
• RPI-based video categorization
• QoS mapping under a given cost constraint from
  video categories to DS classes
• Adaptive packet forwarding mechanism

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RPI-based video categorization

• Different video factors are taken into
  consideration for the RLI association of video
  packet.
• magnitude and direction of the motion vector for
  each MB
• encoding types (intra, intra-refreshed, inter,
  etc)
• initial error due to packet loss

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RPI-based video categorization

• Combine different video factors by different
  weight to get RLI of a packet
• RLIs are categorized into K DS categories using
  Nonuniform quantization of RLI

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QoS mapping from video categories to DS classes

• Formulated into the following optimization
  problem
• QD is quality degradation, average loss
  effect

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QoS mapping

• Equals to minimize the Lagrangian formula

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QoS mapping
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Adaptive packet forwarding mechanism
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Adaptive packet forwarding mechanism

• Combination of adaptive WFQ scheduling and RED
  with in/out bit (RIO)
• Adaptive WFQ
• Providing persistent service differentiation

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Conclusions (1)

• RPI plays a bridging role in enabling the network
  to be content-aware
• Adaptive packet forwarding mechanism provides
  more persistent network DS levels regardless of
  network load fluctuation

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A novel node mechanism for video streaming over
DiffServ2

• Define two types of services High Reliable (HR)
  service, Less Assured (LA) service
• Propose a node mechanism called Selective Pushout
  with Random Early Detection (SPRED)

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A novel node mechanism

• Design objectives
• Core router does not maintain per-flow state
• Packet sequence within each flow should not be
  altered at a node
• Packets from HR service should be delivered as
  reliably as possible
• Packets from TCP traffic should be dropped
  randomly during congestion to avoid global
  synchronization

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A novel node mechanism

• Combination of RED with In/Out and Pushout (PO)
• Architecture

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A case study for aggregation and conformance in
DiffServ3

• Motivation To better understand the impact of
  traffic aggregation on conformance.
• The focus was on identifying the level of
  non-conformance that is introduced into initially
  conformant streams after crossing a DiffServ
  domain.

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A case study for aggregation and conformance in
DiffServ3

• Scenario

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A case study for aggregation and conformance in
DiffServ

• Results and Conclusions
• Basic configuration
• simply decreases network load does not appear to
  be very effective at ensuring egress conformance

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• Neither the number of cross-traffic streams nor
  the number of network hops traversed by the
  tagged stream appear to have a major influence on
  egress conformance
• Two approaches to absorb perturbations introduced
  by network interferences reshaping buffer and
  increase of egress token rate. Increasing egress
  token rate is much less effective than buffering.

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• Variability in Packet Sizes
• In the presence of variable size packets, an
  initially conformed stream of packets can be
  deemed non-conformant on egress, even without any
  network interferences
• The dominant effect in terms of the egress
  conformance of a stream is its internal packet
  variability. In other words, variations of packet
  sizes within a stream have a more pronounced
  effect than the potentially larger network
  perturbations caused by variable packet sizes in
  cross streams

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• Aggregate Contracts
• The number of streams being aggregated, the
  number of cross streams, the number of network
  hops being crossed, and the load on network
  links, all interact with each other in
  determining the egress conformance
• Trade-off that exists between the greater level
  of network perturbations that higher hop counts
  or number of cross streams induces, and the
  greater likelihood that aggregate bursts will be
  broken-up as they traverse the network

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• From simulation, we can see that, increasing in
  hop count typically improve performance, while
  increasing in the number of cross streams usually
  degrade performance

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Pricing, Provision and Peering

• This paper presents a decentralized auction-based
  approach to pricing of edge-allocated bandwidth
  in a differentiated services Internet.
• In the framework, they have one raw-capacity
  seller per network, one broker per service, and
  users, to act as whole-sellers, retailer and
  end-buyers.

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Pricing, Provision and Peering

• dynamic market-pricing of edge-allocated
  bandwidth
• They use game theoretic analysis to get the
  optimal strategies for buyers and brokers.
• the feasibility of maintaining consistent service
  level agreements across interconnected networks
• The good news is that dynamic market-driven
  partitioning of network capacity among services
  appears sustainable.
• The bad news is that very conservatively
  provisioned services can be unstable

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References

• Quality-of-Service Mapping Mechanism for Packet
  Video in Differentiated Services Network, J.
  Shin, J. Kim, and C.-C.J. Kuo, IEEE Transactions
  on Multimedia, Vol. 3, No. 2, June 2001
• A differentiated services architecture for
  multimedia streaming in next generation
  Internet, Y.T. Hou, D. Wu, B. Li, T. Hamada, I.
  Ahmad, and H.J. Chao, Computer Networks 32, 2000,
  pp 185-209
• Aggregation and Conformance in Differentiated
  Service Networks A Case Study, R.A. Guerin and
  V. Pla