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Measurement based traffic engineering
Poul Heegaard,
Telenor R&D / NTNU Dept. Telematics
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Open architecture Performance guarantee Service differentiation
Measurements
Performance optimisationResource allocation
Test labs Production networks
Gilb’s Law:“Anything can be measured in a way that is superior to not measuring it at all.”
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Open architecturePerformance
guaranteeService
differentiations
Measurements
Test labs Production networks
Resource allocation Performance optimisation
Foster rich set applicationsWorldwide commercial
interests
New actors protect investmentsNew cost modelsQoS guarantees
New QoS requirements
New applications, New markets
New QoS requirements
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Performance optimisation
Resource control
Open architecture Performance guarantee Service differentiations
Measurements
Test labsProduction networks
(core/AS, access/SPE/CPE)
Controllable (Protect, Priority, Guarantee)
Proactive (planning, designing)Reactive (monitoring, reconfig)
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Measurements- domain (inter, intra, access, private)- level (physical, network, transport, application)- approach (active, passive)
Open architecture(service innovation, fairness)
Performance guarantee Service differentiation
Performance optimisationResource allocation
Test labs Production network
– SLA fulfilled?– Mechanisms effective? – Effect of new applications?– New applications appeared?– Performance bottlenecks?– Connectivity? – Routing stability?– “Clever” users?– “Malicious” users?– Charging?
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Open architecture Performance guarantee Service differentiations
Measurements
Performance optimisationResource allocation
Test labs
Production networks- redesign, configuration- connectivity- performance assurance- traffic trends - security - input to traffic modelling
Essential: multipurpose measurement architecture
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Multiple measurement objectives
Measurement Application
IP Network QoS & Performance managementMEASUREMENT FUNCTIONS
PrognosisTrends
Traffic matrix
SecurityFraud
DependabilityReliability
Overload(observation and control)
Accounting SLA validation
Planning / Long term operation Medium / Short term operation
Multipurpose measurement probe
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Many options
ADSL 1-
Peering network Our own network
Service provider
POP
DoS attack?traffic volume?
DoS attack?Traffic volume (per customer)?service usage?
End-to-end delay,delay variation (“jitter”), packet loss ratio
Asymmetric traffic?DoS attack?traffic trends?resource (e.g. link) utilisation?
Volume per customer?DoS attack?
Paradigm shift in networking: same platform for all servicesShould also apply to monitoring: same platform for all measurement needs
less than 5% overhead
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Open architecture Performance guarantee Service differentiations
Measurements
Performance optimisationResource allocation
Test labs
Production networks- coarse grained data collection- imprecise active tests- performance demanding- excessive measurement data- increasing measurement needs- measurements by 3rd party - measurement architecture hard
Essential: configurable, precise, up-to-date, available data
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Ex: Delay estimation
• two-way by single point (e.g. in tcp, rtp flows)• one-way by dual point (e.g. inexpensive probes)
upper boundson networklayer delay
protocol effects(e.g. delayed ack)
congestion
no congestion=> perfect match
compare single and dual point estimations
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Ex: flow-sampling
• Data reduction by sampling
0.2 0.4 0.6 0.8 1
20
40
60
80
100 Quantileplot, mpeg traffic
Full trace and 0.099% poisson sampling
Sampled trace
Delay (ms)
Full trace
Quantiles
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Ex: corrected active tests
customer view
provider view
Measure quality any time
Measure quality when service is in use
Validation of delay measured by active tests
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100
200
300
400
500
600
700
800
900
1000
0,5 0,6 0,7 0,8 0,9 1 1,1 1,2 1,3
[ms]
Load level for offered tcp traffic
corrected packet delay
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Test labs
Open architecture Performance guarantee Service differentiations
Measurements
Performance optimisationResource allocation
Production networks
- equipment- mechanisms (e.g. QoS)- configurations- applications- user behaviour
Essential: realistic traffic generator => e.g. GenSyn
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GenSyn - objectives
New network mechanisms
•Controllable•Scalable•Re-producible•Realistic traffic
User behaviour model
Internet protocols
User behaviour model
Internet protocols
New services
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GenSyn – in short
• Java-based, portable traffic generator• Flexible and scalable• Stochastic state models of user behaviour• Link to protocol stack for real packet generation
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Conflicting and interdependent interests
Gordian Knot
simplisity
openess
resource control
QoS guaranteedifferentiation
security
monitoring
segmentation
protection
revenue
real-time
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The solution?