7 Conclusion
The LAN Tomography can provide interesting information about the network. The major
subject of this work is a narrow area of a wide field of application of the Internet
Tomography. The knowledge of the probability distribution of the spent time along a
common path is an important benchmark to test the traffic of the Network. It can be
applied, for example, to find the overloaded paths in the network, or to trace a provisory
state of the network. The purpose of this work is to offer a simple tool to test the network
from another point of view. All the information is obtained without spending much effort
for querying the network. In fact, the user tests the network with simple active probes. The
network is measured without any cooperation from its side. The measurements obtained are
used as data for the Lo Presti algorithm which can be implemented on any computer.
The measurements are obtained by actively testing the network. That is why the user
should choose carefully the size of the probe packets. The impact of an active probe on the
network would be minimized. The experiments conducted in the process of the present
work have shown the dependence of the measured delay on the packet pairs size and the
speed of the link where the packet pair travels. The measured delay is composed of two
kinds of delay. The queuing delay and the transmission delay. The transmission delay
depends on the packet size and the capability of the link on which the packet is sent. An
increase of the packet size causes an increase of the measured delay along the path. The
experiment with an high packet size do not provide good results. There are two reasons for
this effect. The first one is the different impact of the network on the first and the second
member of a packet pair. The difference between their measurements is too high and the
estimate results are not reliable. The second reason is the requirement of the Variable Bin
Size Discrete Model to compute the estimation. In order to obtain a distribution with the
same accuracy, higher values of measurements demand a too high a number of bin B. The
required zone of delays is the smallest part of a spread interval of discretized time. For this
reason, the algorithm introduces useless computational approximations to analyze the zone
known a priori. This results also in a loss of the necessary time to compute the estimate. If
the user needs an “almost” real time estimation, this can be a difficult obstacle to
overcome.
Another possible application of this work is to test the average state of the network by
inferring its average behavior. The Unbiased property leads to a major consistency in
obtaining a single estimation. For this reason the same experiment can be repeated more
times in the same hour so that an average statistic of a specific hour can be obtained. An
average analysis can be conducted also at different times of a day, obtaining information of
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the state of the network in general time. A daily average behavior then can be estimated by
multiplying the single average statistics. The results should provide an estimate of the
regular state of the network.
The Internet Tomography is so far is typically applied in wide area network and it
represents an important inference tools to analyze the network. The aim of this work is to
investigate the utility of an application of tomography in a local area network.
The WAN Tomography approach, is very complex and requires reliable techniques to
probe the network. An active probe can load the network, which should not be involved in
the inference process. In a link-level delay estimation, the required one way delay
measurements, can not to be easy to obtain, and a synchronization process of the end hosts
is necessary. Besides, the information of the network are shared by different providers and
this aspect increases the difficulty to obtain the measurements. Finally, the computational
aspect of WAN tomography, is very critic and depends in particular, on the dimension of
the network and on inference model adopted. These are some aspects that represent the
stunted to pay to obtain good results which can be provided by the Network Tomography.
In a LAN tomography the major part of these problems can be solved more easily. The
LAN is a closed network and this represents an important advantage. The dimension is
known and there is a direct contact of the user with the network. The aim of this work is to
provide the simplest tool to apply the tomography in a LAN. This is possible but by using
some simplifications. For example in the link level delay estimation in a LAN, the RTT
replaces the one way delay of the WAN tomography. This aspect represents a big
advantage but it remains also a simplification. The RTT in a WAN ambient cannot be a
reliable measurement. Generally, the first and second packet of a packet pairs in fact, do
not follow the same path to go and to come back from the end host. In a LAN this is more
often the case possible because the topology of the network is more static.
In a LAN the MLE can be implemented for the small dimension of the network. In WAN
ambient the MLE becomes infeasible for the computational complexity and it is replaced
by the MPLE.
The algorithm of the Fixed Bin Size Model by Lo Presti is optimum for small experienced
delay in a LAN. Usually there is not a consistent jitter in the measurements. The measured
delays vary in a small range close the average delay. If the network is overload the jitter
increases and a change of the delay distribution can be detected.
The LAN Tomography can be applied without requiring any dedicated operative system of
the end hosts. The Ping program is a common program which can be used with the majority
of hosts. The measurements can be obtained easily with Ping and be provided to the
algorithm. The algorithm works independently and carry out the estimations.
The Internet Tomography is very wide field of studies and a lot of applications in LAN can
be implemented. This work presents one of the applications and explains that the
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7 Conclusion
“inference theory ” represents an important instrument to effectively manage the near
future and the fast growth of the Internet world.
Acknowledgement
I would like to thanks Prof. P. Tran-Gia, Dr. K. Tutschku, Prof. S. Giordano and Dr. R. G.
Garroppo who gave me the possibility to work at the Department of Distributed System of
the University of Wuerzburg. A special thanks to Dr. Kurt Tutschku and his precious
advice to conduct the working process in the right direction and time framework. The
cooperation with Francesco Lo Presti, one of the most important researcher of Internet
Tomography, allowed to provide more professional prestige to the present work. I would
like to thank Martin Brotzeller and Ulrich Spoerlein for their very helpful comments on the
programming work and Ekaterina Kojevatova for her help and patience to correct the text.
Last, but not least, I would like thank to Nicola Bonelli of the Network Research Group
from the University of Pisa for the useful suggestions to modify the Ping program, Björn
auf dem Graben for the configuration of the Router Lab to measure the network, R. Henjies
and Andreas Binzenhofer for their constant availability and helpfulness.
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