PathChirp Efficient Available Bandwidth Estimation Vinay Ribeiro Rice University Rolf Riedi Jiri...

Post on 31-Mar-2015

218 views 2 download

Tags:

Transcript of PathChirp Efficient Available Bandwidth Estimation Vinay Ribeiro Rice University Rolf Riedi Jiri...

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-pairs

Packet 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 Methodology

I. 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

REqq

REqq

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 Accuracy

pathchirp pathload pathChirp10-90%

pathloadAvg.min-max

30Mbps 0.35MB 3.9MB 19-29Mbps 16-31Mbps

50Mbps 0.75MB 5.6MB 39-48Mbps 39-52Mbps

70Mbps 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