Efficient Available Bandwidth Estimation with PathChirp Tool for Network Monitoring and Route Selection
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PathChirp is a probing tool that estimates available bandwidth along end-to-end paths in networks. It uses the principle of Self-Induced Congestion to measure available bandwidth accurately with minimum probing load, making it ideal for various applications like network monitoring and congestion control.
Efficient Available Bandwidth Estimation with PathChirp Tool for Network Monitoring and Route Selection
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Presentation Transcript
pathChirpEfficient 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) + 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 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) • Robustto multiple congested links • No topology information(e.g. link speeds) • Robustto 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
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 Trains of Packet-Pairs (TOPP)[Melander et al]
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 • Exponentiallydecrease packet spacing withinpacket 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 validexcursions
Valid excursion increasing queuing delay • Valid excursion decreasing queuing delay • Invalid excursions • Last excursion Setting Per-Packet Pair Available Bandwidth
pathChirp Tool • UDPprobe 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 • 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
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