Video Streaming over Diff Serv and some other

Video Streaming over Diff. Serv and some other Issues Presented by Wei

Outline n n A framework for video streaming over Diff. Serv network A novel node mechanism for video streaming over Diff. Serv network A case study for aggregation and conformance in Diff. Serv network Pricing, Provisioning and Peering of Diff. Serv network

Framework for Video over Diff. Serv[1] n This paper presents a framework for qualityof-service mapping between categorized packet video and relative Diff. Serv network. n n n RPI-based video categorization Qo. S mapping under a given cost constraint from video categories to DS classes Adaptive packet forwarding mechanism

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

RPI-based video categorization n n 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

Qo. S mapping from video categories to DS classes n Formulated into the following optimization problem QD is quality degradation, effect average loss

Qo. S mapping n Equals to minimize the Lagrangian formula

Qo. S mapping

Adaptive packet forwarding mechanism

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

Conclusions (1) n n 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

A novel node mechanism for video streaming over Diff. Serv[2] n n 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)

A novel node mechanism n Design objectives: n n 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

A novel node mechanism n n Combination of RED with In/Out and Pushout (PO) Architecture

A case study for aggregation and conformance in Diff. Serv[3] n n 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 Diff. Serv domain.

A case study for aggregation and conformance in Diff. Serv[3] n Scenario

A case study for aggregation and conformance in Diff. Serv n Results and Conclusions: n Basic configuration n simply decreases network load does not appear to be very effective at ensuring egress conformance

n n 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.

n Variability in Packet Sizes n n In the presence of variable size packets, an initially conformed stream of packets can be deemed nonconformant 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

n Aggregate Contracts n n 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

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

Pricing, Provision and Peering n n This paper presents a decentralized auctionbased approach to pricing of edge-allocated bandwidth in a differentiated services Internet. In the framework, they have one rawcapacity seller per network, one broker per service, and users, to act as whole-sellers, retailer and end-buyers.

Pricing, Provision and Peering n dynamic market-pricing bandwidth n n of edge-allocated 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 n n 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

References n n n “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