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Methodology for Parameterisation of Large Scale Network Simulations
Citation Link: https://doi.org/10.15480/882.34
Other Titles
Methodologie der Parametrisierung von Large-Scale-Netzwerk-Simulationen
Publikationstyp
Doctoral Thesis
Date Issued
2003
Sprache
English
Author(s)
Advisor
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2003-11-27
Institut
TORE-DOI
Citation
Dissertation : Mensch & Buch, 2003
Network providers are confronted with the optimisation or extension of
existing networks. This leads to new challenges for simulation-based
network dimensioning. The first challenge is the realistic simulation
of the existing network, where topology information and traffic
measurements have to be considered. The second challenge is to predict
how changes of the existing network will affect its performance: link
capacities, queue management algorithms etc. are subject to changes to
adapt the network to changing traffic requirements. The best strategy
for enhancing or extending the network under consideration can be
found by comparing the resulting benefits and disadvantages between
the existing network and new alternatives.
The simulation of existing networks is an inverse problem: (i) the
network description and some measurements are given from the network
provider; (ii) the number and the behaviour of clients must be derived
from the given parameters. Considering this problem was motivated by
an industry project "ERNANI" funded by the "Deutsches Forschungsnetz"
(DFN) and the German Telekom.
The author proposes a new methodology to solve the inverse problem.
First, an algorithm for the allocation of clients is proposed. This
algorithm efficiently controls the average traffic intensity. Second,
a method is developed for matching higher-order moments of the
simulated traffic to measurements made in existing networks. Two
higher moment parameters were selected, that are of major importance
in network engineering: the coefficient of variation and the Hurst parameter.
Realistic network simulations are characterised by high complexity
because internal states of protocols must be stored for each
connection. Therefore, memory requirements and simulation speed are
major issues in such simulations. One solution for this problem is to
reduce the number of clients by increasing the activity of each client
in order to keep the traffic characteristics unchanged. To asses the
applicability and performance of this solution, critical network
parameters are estimated as a function of the number of clients. The
parameters considered are: average link load, loss probability,
coefficient of variation of the packet inter-arrival times, Hurst
parameter and average end-to-end delay. It is shown in this work that
the number of clients, as well as the required memory, could be
reduced by a factor of 4-8 without significant impact on the studied
parameters. Reducing the number of clients by a factor of 8 the
simulation speed increased by approximately 33 %.
This work represents a major step towards realistic modelling and
simulation of existing networks. The simulation results based on the
presented methodology are very promising. The successful increase of
the simulation efficiency represents one step towards the realistic
simulation of current and future multi-Gbit networks.
existing networks. This leads to new challenges for simulation-based
network dimensioning. The first challenge is the realistic simulation
of the existing network, where topology information and traffic
measurements have to be considered. The second challenge is to predict
how changes of the existing network will affect its performance: link
capacities, queue management algorithms etc. are subject to changes to
adapt the network to changing traffic requirements. The best strategy
for enhancing or extending the network under consideration can be
found by comparing the resulting benefits and disadvantages between
the existing network and new alternatives.
The simulation of existing networks is an inverse problem: (i) the
network description and some measurements are given from the network
provider; (ii) the number and the behaviour of clients must be derived
from the given parameters. Considering this problem was motivated by
an industry project "ERNANI" funded by the "Deutsches Forschungsnetz"
(DFN) and the German Telekom.
The author proposes a new methodology to solve the inverse problem.
First, an algorithm for the allocation of clients is proposed. This
algorithm efficiently controls the average traffic intensity. Second,
a method is developed for matching higher-order moments of the
simulated traffic to measurements made in existing networks. Two
higher moment parameters were selected, that are of major importance
in network engineering: the coefficient of variation and the Hurst parameter.
Realistic network simulations are characterised by high complexity
because internal states of protocols must be stored for each
connection. Therefore, memory requirements and simulation speed are
major issues in such simulations. One solution for this problem is to
reduce the number of clients by increasing the activity of each client
in order to keep the traffic characteristics unchanged. To asses the
applicability and performance of this solution, critical network
parameters are estimated as a function of the number of clients. The
parameters considered are: average link load, loss probability,
coefficient of variation of the packet inter-arrival times, Hurst
parameter and average end-to-end delay. It is shown in this work that
the number of clients, as well as the required memory, could be
reduced by a factor of 4-8 without significant impact on the studied
parameters. Reducing the number of clients by a factor of 8 the
simulation speed increased by approximately 33 %.
This work represents a major step towards realistic modelling and
simulation of existing networks. The simulation results based on the
presented methodology are very promising. The successful increase of
the simulation efficiency represents one step towards the realistic
simulation of current and future multi-Gbit networks.
Subjects
telecommunication network
network simulation
network topology
DDC Class
004: Informatik
620: Ingenieurwissenschaften
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