pathChirp

Efficient Available Bandwidth Estimation

Vinay RibeiroRice University

Rolf Riedi Jiri NavratilRich Baraniuk Les Cottrell

(Rice) (SLAC)

Network Model

Packet delay = constant term (propagation,

service time) + variable term (queuing delay)

• End-to-end paths– Multi-hop– No packet reordering

• Router queues– FIFO– Constant service rate

Available Bandwidth• Unused capacity along

path

)],0[(min],0[number queue T

TACTB iii

Available bandwidth:

• Goal: use end-to-end probing to estimate available bandwidth

Applications

• Network monitoring

• Server selection• Route selection (e.g. BGP)

• SLA verification• Congestion control

Available Bandwidth Probing Tool

Requirements• Fast estimate within few RTTs

• Unobtrusive introduce light probing load

• Accurate

• No topology information (e.g. link speeds)

• Robust to multiple congested links

• No topology information (e.g. link speeds)

• Robust to multiple congested links

Principle of Self-Induced Congestion

• Advantages– No topology information required– Robust to multiple bottlenecks

• TCP-Vegas uses self-induced congestion principle

Probing rate < available bw no delay increase

Probing rate > available bw delay increases

Trains of Packet-Pairs (TOPP) [Melander et al]

)( st)( rt

• Vary sender packet-pair spacing• Compute avg. receiver packet-pair spacing• Constrained regression based estimate

• Shortcoming: packet-pairs do not capture temporal queuing behavior useful for available bandwidth estimation Packet-pairsPacket train

Pathload [Jain & Dovrolis]

• CBR packet trains • Vary rate of successive trains • Converge to available bandwidth

• Shortcoming Efficiency: only one data rate per train

Chirp Packet Trains

• Exponentially decrease packet spacing within packet train

• Wide range of probing rates• Efficient: few packets

100Mbps-1 packets, 134.1

Chirps vs. Packet-Pairs• Each chirp train of N packets contains N-1 packet pairs at

different spacings

• Reduces load by 50% – Chirps: N-1 packet spacings, N packets– Packet-pairs: N-1 packet spacings, 2N-2 packets

• Captures temporal queuing behavior

Chirps vs. CBR Trains• Multiple rates in each chirping train

– Allows one estimate per-chirp

– Potentially more efficient estimation

CBR Cross-Traffic Scenario

• Point of onset of increase in queuing delay gives available bandwidth

Bursty Cross-Traffic Scenario

• Goal: exploit information in queuing delay signature

PathChirp MethodologyI. Per-packet pair

available bandwidth, (k=packet number)

II. Per-chirp available bandwidth

III. Smooth per-chirp estimate over sliding time window of size

kk

kkk

t

tED

kE

Self-Induced Congestion Heuristic

• Definitions: delay of packet k inst rate at packet k

kkkk

kkkk

REqqREqq

1

1

kqkk tR size/packet

Excursions

• Must take care while using self-induced congestion principle• Segment signature into excursions from x-axis• Valid excursions are those consisting of at least “L” packets• Apply only to valid excursions

kk RE

Setting Per-Packet Pair Available Bandwidth

• Valid excursion increasing queuing delaykk

kk

RE

RE

nk

kk

RE

RE

• Valid excursion decreasing queuing delay

nk

kk

RE

RE

•Last excursion• Invalid excursions

nk RE

pathChirp Tool• UDP probe packets• No clock synchronization required, only uses

relative queuing delay within a chirp duration • Computation at receiver• Context switching detection• User specified average probing rate

• open source distribution at spin.rice.edu

Performance with Varying Parameters

• Vary probe size, spread factor

• Probing load const.• Mean squared error

(MSE) of estimates Result: MSE decreases with increasing probe size, decreasing spread factor

Multi-hop Experiments

• First queue is bottleneck

• Compare– No cross-traffic at

queue 2– With cross-traffic

at queue 2• Result: MSE close in

both scenarios

Internet Experiments

• 3 common hops between SLACRice and ChicagoRice paths

• Estimates fall in proportion to introduced Poisson traffic

Comparison with TOPP

30% utilization

• Equal avg. probing rates for pathChirp and TOPP

• Result: pathChirp outperforms TOPP

70% utilization

Comparison with Pathload • 100Mbps links• pathChirp uses 10

times fewer bytes for comparable accuracy

Available bandwidth

Efficiency Accuracypathchirp pathload pathChirp

10-90%pathloadAvg.min-max

30Mbps 0.35MB 3.9MB 19-29Mbps 16-31Mbps50Mbps 0.75MB 5.6MB 39-48Mbps 39-52Mbps70Mbps 0.6MB 8.6MB 54-63Mbps 63-74Mbps

Conclusions• Chirp trains

– Probe at multiple rates simultaneously– Efficient estimates

• pathChirp– Self-induced congestion– Excursion detection

• Experiments– Internet experiments promising– Large probe packet size, small spread factor better– Outperforms existing tools

• open-source code is available at spin.rice.edu

• Demo during 10:30a.m. break