pathChirp Efficient Available Bandwidth Estimation

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pathChirp Efficient Available Bandwidth Estimation
pathChirp Efficient Available Bandwidth Estimation
Presentation transcript:

pathChirp Efficient Available Bandwidth Estimation Vinay Ribeiro Rice University Rolf Riedi Jiri Navratil Rich Baraniuk Les Cottrell (Rice) (SLAC)

Network Model End-to-end paths Router queues Multi-hop No packet reordering Router queues FIFO Constant service rate Packet delay = constant term (propagation, service time) + variable term (queuing delay)

Available Bandwidth Available bandwidth: Unused capacity along path Available bandwidth: Goal: use end-to-end probing to estimate available bandwidth

Applications Server selection Route selection (e.g. BGP) Network monitoring 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 Probing rate < available bw  no delay increase Probing rate > available bw  delay increases Advantages No topology information required Robust to multiple bottlenecks TCP-Vegas uses self-induced congestion principle

Trains of Packet-Pairs (TOPP) [Melander et al] Shortcoming: packet-pairs do not capture temporal queuing behavior useful for available bandwidth estimation Vary sender packet-pair spacing Compute avg. receiver packet-pair spacing Constrained regression based estimate Packet train Packet-pairs

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

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 Per-packet pair available bandwidth, (k=packet number) Per-chirp available bandwidth Smooth per-chirp estimate over sliding time window of size

Self-Induced Congestion Heuristic Definitions: delay of packet k inst rate at packet k

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

Setting Per-Packet Pair Available Bandwidth Valid excursion increasing queuing delay Last excursion Valid excursion decreasing queuing delay Invalid excursions

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 SLACRice and ChicagoRice paths Estimates fall in proportion to introduced Poisson traffic

Comparison with TOPP Equal avg. probing rates for pathChirp and TOPP Result: pathChirp outperforms TOPP 30% utilization 70% utilization

Comparison with Pathload 100Mbps links pathChirp uses 10 times fewer bytes for comparable accuracy Available bandwidth Efficiency Accuracy pathchirp pathload pathChirp 10-90% Avg.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 pathChirp Experiments 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