Summary of D1.3
Manuel Graña (UPV)
for
Midterm Review meeting EC, Brussels
March 31, 2014
• Contents
– Queuing systems modeling
– Role of performance modeling in SandS
– Introductory models
• Model 1: simple aggregate
• Model 2: the effect of learning and recipe innovation
– Explanation of delay in delivery
Midterm Review Meeting, March 31, 2014
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• Queuing systems modelling
– Prediction of dynamic features
• Response times
• Congestion and queue lengths at critical points
– Stochastic models
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Arrival processes
Service processes
Network of nodes with routing probabilities
Specific features outside mathematical modelling
– Resolution
• Analytical
• Simulation
Midterm Review Meeting, March 31, 2014
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• Role of performance modelling in SandS
– Requirements of low bandwidth occupancy
• No conflict with other uses of network at home
– Effect of critical elements of the system
• Learning/innovation process
• Response time of database queries
– Combined with workload tests
• For model tuning
• For extrapolation
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• Introductory models
• Simple aggregated model
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• Simple model, some results
Short term dependency on service times
at each node
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• Response time versus probability of creating a
new recipe
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• Second model: decomposing the recipe
creation process
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• Second model: some results
High correlation of
response time and
probability of
needing to create
a recipe
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• The effect of the probability of creating a good
recipe
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• Some conclusions
– The system does not work on the limit, so no big
problems may be expected
– The learning process can be a bottleneck
• If the learning time grows
• If the probability of bad recipes is high
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• Source of delay in the deliverable publication.
– Some misunderstanding about content
– Attempt to coordinate with other performance
measuring deliverables.
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