OverQos: An Overlay based Architecture for Enhancing Internet Qos

L Subramanian*, I Stoica*, H Balakrishnan+, R Katz**UC Berkeley, MIT+

USENIX NSDI’04, 2004

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Outline

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

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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.

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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

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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

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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

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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

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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 tr(t): Fraction of redundancy traffic

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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 cmin

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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

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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 e

xpect 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

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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-ratec: available bandwidth

p: loss rateb: maximum sending rate

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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 r1 = 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

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Streaming Media Application

Two enhancements The quality can be enhanced by converting burst

y 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

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Streaming Media ApplicationEvaluation

Perceptual Evaluation of Speech Quality (PESQ)(5 is ideal)

Increase0.15 – 0.2

Average loss rate Mazu-Korea – 2% Intel-Lulea – 3%

Streaming Audio

MPEG streaming

Not only improves the quality in the average casebut also the minimum quality of a stream

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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 siz

e of the burst at the overlay node Identify control packets based on packet size an

d not drop these packets

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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

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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

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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%

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Statistical Bandwidth Guarantees

Monitor 83 unique virtual linksu = 0.01 and u = 0.005

The value of cmin is greater than 100Kbpsfor more than 80% of the links

N-TCP, N = 10

Stability of cmin

1) The value of cmin 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 cmin based on a history of 200 seconds

The average sending rate of N-TCP is between 120Kbps to 2Mbps

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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

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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-hop2) Adding new OverQoS nodes

increasing limited delay

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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 con

sisting 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

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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 OverQ

oS nodes in the network