OverQos: An Overlay based Architecture for Enhancing Internet Qos L Subramanian*, I Stoica*, H Balakrishnan +, R Katz* *UC Berkeley, MIT + USENIX NSDI’04, 2004

2 Outline Introduction OverQos Architecture Controlled-Loss Virtual Link (CLVL) OverQoS Implementation Two Sample Application Evaluation Conclusions

3 Introduction Today’s Internet still continues to provide only a best-effort service. The main reason is the requirement of these proposals that all network elements implement QoS mechanisms. The authors propose OverQoS, an overlay based QoS architecture for enhancing Internet QoS.

4 Introduction (cont.) Enhancements:  Smoothing losses Reduce or even eliminate the loss bursts by smoothing packet losses across time  Packet prioritization Protect important packets  Statistical Bandwidth and Loss Guarantees

5 OverQoS Architecture (1/3) Assumptions  The placement of overlay nodes is pre-specified  The end-to-end path on top of an overlay network is fixed Using existing approaches like RON to determine the overlay path. Terms  Virtual link – The IP path between two overlay nodes  Bundle – A stream of application data packets carried across the virtual link

6 OverQoS Architecture (2/3) Overlay-based QoS challenges  Node Placement and Cross Traffic  Fairness Should not hurt the cross traffic  Stability Many virtual links overlapping on congested physical links should be able to co-exist

7 OverQoS Architecture (3/3) A Solution builds on two principles  Bundle loss control Using controlled-loss virtual link (CLVL) to bound the loss rate  Resource management within a bundle Control the loss and bandwidth allocations

8 Bundle Loss Control The CLVL provides a loss rate bound, q.  Using a combination of FEC and ARQ  The bandwidth overhead should be minimized The total traffic consists of:  The traffic of the bundle  The redundancy traffic The available bandwidth for the flows in the bundle b(t): Traffic bound at time t r(t): Fraction of redundancy traffic

9 Resource Management within a Bundle If the traffic arrival rate is larger than available bandwidth c, the extra traffic is dropped at the entry overlay node  With priority Statistical bandwidth guarantees , where u represents the probability of not meeting the bandwidth guarantee  As long as the total allocated bandwidth is less than c min

10 Overall picture Application-OverQoS Interface  It needs to tunnel its packets through the overlay network using an OverQoS proxy  The proxy is responsible for signaling the application specific requirements to OverQoS OverQoS proxy is application specific

11 Discussion End-to-end Recovery vs. Overlay CLVL  Using FEC to apply end-to-end loss control is far more expensive than on an aggregate level  With a better distribution of overlay nodes, they expect the overlay links to have much smaller RTTs than end-to-end RTTs ARQ recovery is better in overlay-level Delay guarantees  Overlay has no control in queuing delays Over-provisioning  Overlay are the right platform for translating intra domain QoS to end-to-end QoS guarantees

12 Controlled-Loss Virtual Link (CLVL) Estimating b  Based on an N-TCP pipe abstraction which provides a bandwidth which is N times the throughput of a single TCP connection. Use MulTCP to emulate the behavior N is equal to the number of flows in the bundle Node Architecture q: target loss-rate c: available bandwidth p: loss rate b: maximum sending rate

13 Achieving target loss rate q  FEC vs. ARQ trade-off Bandwidth overhead and packet recovery time  FEC+ARQ based CLVL Restrict # of retransmissions to at most one The expected packet loss rate The expected bandwidth overhead The optimal solution is when r 1 = 0 Controlled-Loss Virtual Link (CLVL) (cont.)  After two rounds  Goal  Minimizes r is the redundancy factor

OverQoS Implementation Application-dependent proxy Choosing parameters  N as the average number of flows observed over a larger period of time  q = 0.1% Startup phase  Using a slow-start phase to estimate the initial value of b FEC implementation  Operating on small window sizes (n < 1000)  coding is not a bottleneck

15 Streaming Media Application Two enhancements  The quality can be enhanced by converting bursty losses into smooth losses  for streaming audio  Recovering packets preferentially can improve the quality  for MPEG streaming Not consume any additional bandwidth  Retransmits an important lost packet and drops a later lesser important packet

16 Streaming Media Application Evaluation Perceptual Evaluation of Speech Quality (PESQ) (5 is ideal) Increase 0.15 – 0.2 Average loss rate Mazu-Korea – 2% Intel-Lulea – 3% Streaming Audio MPEG streaming Not only improves the quality in the average case but also the minimum quality of a stream

17 Counterstrike Application Problem  Client unable to connect to the server  Cause skips or get disconnected Alleviate the problem of bursty losses by performing:  Recover from bursty network losses by using an FEC+ARQ based CLVL  Smoothly drop data packets equivalent to the size of the burst at the overlay node  Identify control packets based on packet size and not drop these packets

18 Counterstrike Application Evaluation Sequence number plot illustrating smoothing of packet losses using OverQoS  Smoothing losses works well only when the bursty loss-periods are relatively short by compensating  Unable to achieve the target loss-rate due to congestion periods with very high loss-rates 10% loss-rate

19 Evaluation Methodology  Wide-Area Evaluation Testbed RON and PlanetLab – use 19 diverse nodes  Simulation Environment Ns-2 – a single congested link of 10 Mbps where they vary the background traffic  Long lived TCP connections  Self similar traffic  Web traffic

20 Statistical Loss Guarantees Simulations Wide Area Evaluation  Achieve target over 80 of the 83 virtual links  The causes of the other 3 virtual links Short outages – a period of time all packets are lost (< 5s) Bi-modal loss distributions – bursty losses q = 0.1%

21 Statistical Bandwidth Guarantees Monitor 83 unique virtual links u = 0.01 and u = The value of c min is greater than 100Kbps for more than 80% of the links N-TCP, N = 10  Stability of c min 1)The value of c min is very stable, which does not deviate more than 10% around its mean 2)Set P = 1%, the actual value is no more than 1.3% Calculate c min based on a history of 200 seconds The average sending rate of N-TCP is between 120Kbps to 2Mbps

22 OverQoS Cost Overhead Characteristics The difference between avg. loss & FEC+ARQ is the amount of FEC used in the second round The burstier the background traffic, the higher the amount of FEC required to recover from these losses

23 OverQoS Cost (cont.) Delay Characteristics  Two reasons for increasing delay The recovery process Support in-sequence delivery of packets Three different models (a)No packet ordering (b)End-to-end ordering (c)Hop-by-hop ordering 1)E2E is better than Hop-by-hop 2)Adding new OverQoS nodes increasing limited delay

24 Fairness and Stability Three OverQoS bundles (with N=2, N=4, N=8) compete on a shared bottleneck under two different scenarios  No cross-traffic  Cross-traffic consisting of five long lived TCPs 1)Three OverQoS bundles co-exist with each other and with the background traffic 2)The ratio of throughputs of the three bundles is preserved

25 Conclusions OverQoS can enhance Internet QoS without any support from the underlying IP network OverQoS is able to achieve the three enhancements with little (i.e., 5%) or no extra bandwidth. Future work  Combine admission control and path selection  Determine the “optimal” placement of the OverQoS nodes in the network