pathchirp efficient available bandwidth estimation
DESCRIPTION
pathChirp Efficient Available Bandwidth Estimation. Vinay Ribeiro Rice University Rolf Riedi Jiri Navratil Rich Baraniuk Les Cottrell (Rice) (SLAC). Network Model. Packet delay = constant term (propagation, service time) - PowerPoint PPT PresentationTRANSCRIPT
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pathChirp
Efficient Available Bandwidth Estimation
Vinay RibeiroRice University
Rolf Riedi Jiri NavratilRich Baraniuk Les Cottrell
(Rice) (SLAC)
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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
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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
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Applications
• Network monitoring
• Server selection• Route selection (e.g. BGP)
• SLA verification• Congestion control
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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
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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
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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
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Pathload [Jain & Dovrolis]
• CBR packet trains • Vary rate of successive trains • Converge to available bandwidth
• Shortcoming Efficiency: only one data rate per train
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Chirp Packet Trains
• Exponentially decrease packet spacing within packet train
• Wide range of probing rates• Efficient: few packets
100Mbps-1 packets, 134.1
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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
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Chirps vs. CBR Trains• Multiple rates in each chirping train
– Allows one estimate per-chirp
– Potentially more efficient estimation
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CBR Cross-Traffic Scenario
• Point of onset of increase in queuing delay gives available bandwidth
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Bursty Cross-Traffic Scenario
• Goal: exploit information in queuing delay signature
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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
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Self-Induced Congestion Heuristic
• Definitions: delay of packet k inst rate at packet k
kkkk
kkkk
REqqREqq
1
1
kqkk tR size/packet
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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
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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
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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
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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
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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
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Internet Experiments
• 3 common hops between SLACRice and ChicagoRice paths
• Estimates fall in proportion to introduced Poisson traffic
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Comparison with TOPP
30% utilization
• Equal avg. probing rates for pathChirp and TOPP
• Result: pathChirp outperforms TOPP
70% utilization
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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
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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