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Experimental and Analytical Evaluationof Available Bandwidth Estimation Tools
Cesar D. Guerrero and Miguel A. Labrador
Department of Computer Science & Engineering
University of South Florida
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Outline
• Motivation• Problem• Testbed Description• Analytical Model• Target Tools• Performance Evaluation• Conclusions
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MotivationWhy to evaluate available bandwidth tools?
• Available bandwidth to improve network applications performance.
• Applications different time, accuracy, and overhead from estimators.
• Evaluation determine whether a tool is suitable for an application.
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ProblemWhat issues do we want to solve?
• Evaluate tools over the same variable network conditions
• Analytical model to have a theoretical value to compare with
Topology Link capacities Packet loss rate Delay
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Testbed DescriptionArchitecture
• Client and server hosting bandwidth estimation tools
• Intermediate nodes hosting a packet shaper and a traffic generator
• Phython applications running in all the machines to automatically perform experiments.
• Internet connected
ClientServer
192.168.3.0/24 192.168.2.0/24 192.168.1.1/24192.168.4.0/24
192.168.0.0/24
Probing packets Cross Traffic
Link A Link B Link C Link D
Low cost
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Analytical ModelJackson Network
• Eight M/M/1 queues model input and output packet flows.
• The Jackson model gives the average arrival rate to a node
λj = γj + Σλiθij
• The available bandwidth is the minimum non utilized capacity of the queues associated to the links:
A = mini=1,3,5,7 (Ai) = mini=1,3,5,7 (1-ρi)
Client Server
1 2 3 4 5 6 7
8Cross Traffic
λ0
λ1 λ2 λ3 λ4 λ5λ7λ6
γ1 γ3 γ5 γ7
λ8
Probing packets
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Target ToolsEstimation Approaches
Probe Rate Model
• Pathload.
• TOPP
• Pathchirp
• PTR
Probe Gap Model
• IGI
• Delphy
• Spruce
• IGI• Pathload
• Spruce
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Target ToolsPathload
• Fleet of probing streams are sent to fill the available bandwidth.
• The one-way delay increases when the rate of the probing traffic is higher that the available bandwidth.
• In the gray region, the tool reports the available bandwidth
grey region
Figure copied from the paper “Pathload: A Measurement Tool for End-to-end Available Bandwidth” by M. Jain and C. Dovrolis
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Target ToolsIGI
• Estimates the cross traffic as a function of the amount of traffic inserted between a packet pair.
• Available bandwidth is given by the average rate of the packet train when the initial packet gap is equal to the output gap.
turning point
Figure copied from the paper “Evaluation and Characterization of Available Bandwidth Probing Techniques” by N. Hu and P. Steenkiste
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Target ToolsSpruce
• Probing packets are sent with an intra-pair gap (Δin) equal to the narrow link transmission time of a 1500B packet (to guarantee that the pair will be in the queue at the same time)
• Cross traffic is measured using the dispersion of the probing packets
(Δout) calculated at the receiver.
• It requires a previous calculation of the tight link capacity (C)
in
inoutCA 1
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Performance EvaluationExperiments
• Metrics: accuracy, time, overhead
• 28 network scenarios: link capacities from 1 to 10 Mbps and from 10 to 100 Mbps
• Each scenario with four cross traffic loads: 0%, 25%, 50%, and 75% of the capacity
• Every estimation was performed 35 times
• Accuracy plots have a 95% confidence interval
11760 experiments
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Performance EvaluationAccuracy with 75% of the capacity as cross traffic
Estimated available bandwidth / total bandwidth (capacity)
Pathload IGI Spruce
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Performance EvaluationRelative Error
A
AA
analytical
analyticalalexperimentβ
Pathload IGI Spruce
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Performance EvaluationConvergence Time
Pathload IGI Spruce
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Performance EvaluationOverhead
Pathload IGI Spruce
Probing traffic / total bandwidth (capacity) in the tight link
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Conclusions
• Main contributions:
Low cost and flexible testbed to evaluate estimation tools in a controlled network.
Analytical model to fairly compare the tools accuracy with a theoretical value.
• Regarding to the tools evaluation:
Pathload is the most accurate tool but the slowest to convergeIGI is the fastest tool but the least accurateSpruce is the least intrusive tool with intermediate accuracy and
convergence time.
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Experimental and Analytical Evaluationof Available Bandwidth Estimation Tools
Cesar D. [email protected]
Miguel A. [email protected]
Department of Computer Science & Engineering
University of South Florida
