1. Video Streaming over DiffServ and some other Issues Presented by Wei Wei

2. 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

3. Framework for Video over DiffServ [1] 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

5. 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

6. 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

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

8. QoS mapping Equals to minimize the Lagrangian formula

9. QoS mapping

10. Adaptive packet forwarding mechanism

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

12. 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

13. A novel node mechanism for video streaming over DiffServ [2] 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)

14. 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

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

17. A case study for aggregation and conformance in DiffServ [3] 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.

18. A case study for aggregation and conformance in DiffServ [3] Scenario

19. 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

21. 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.

22. 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

24. 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

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

26. 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.

28. 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

29. 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