Profiling plots and results ready for M4 delivery

This commit is contained in:
Jaume Nin
2011-12-02 16:33:07 +01:00
parent 62b37620e9
commit 7a5ebed9ce
10 changed files with 3290 additions and 633 deletions

View File

@@ -1,6 +1,6 @@
EPSTOPDF = epstopdf
DIA = dia
CONVERT = convert
CONVERT = convert -density 250
SOURCE = source
@@ -13,6 +13,8 @@ IMAGES_EPS = \
$(FIGURES)/ff-example.eps \
$(FIGURES)/lte-enb-architecture.eps \
$(FIGURES)/lte-ue-architecture.eps \
$(FIGURES)/epc-profiling-scenario.eps \
$(FIGURES)/eutran-profiling-scenario.eps \
$(FIGURES)/lte-interference-test-scenario.eps
# specify figures for build process (all eps figures)
@@ -21,8 +23,11 @@ GRAPHS_EPS = \
$(FIGURES)/lenaThrTestCase1.eps \
$(FIGURES)/lenaThrTestCase2.eps \
$(FIGURES)/runningTime10s.eps \
$(FIGURES)/epcRunningTime.eps \
$(FIGURES)/propagationModel.eps \
$(FIGURES)/simulationTime.eps \
$(FIGURES)/epcSimulationTime.eps \
$(FIGURES)/epcEutranRunningTime.eps \
$(FIGURES)/profiling-memory.eps \
$(FIGURES)/lte-rlc-implementation-model.eps \
$(FIGURES)/lte-rlc-data-txon-dl.eps \

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@@ -0,0 +1,848 @@
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Overview and objectives
***********************
The main profiling objective is to assess the simulator performance on a broad set of scenarios. This evaluation provides reference values for simulation running times and memory consumption figures. It also helps to identify potential performance improvements and to check for scalability problems when increasing the number of eNodeB and the number of UEs attached to each eNodeB.
The main objective of the profiling carried out is to assess the simulator performance on a broad set of scenarios. This evaluation provides reference values for simulation running times and memory consumption figures. It also helps to identify potential performance improvements and to check for scalability problems when increasing the number of eNodeB and UEs attached to those.
In the following sections, a detailed description of the general profiling framework employed to perform this profiling study is introduced. It also introduces the details of the main tests performed and its results are evaluated.
In the following sections, a detailed description of the general profiling framework employed to perform the study is introduced. It also includes details on the main performed tests and its results evaluation.
Framework description
*********************
Simulation script
~~~~~~~~~~~~~~~~
Simulation scripts
~~~~~~~~~~~~~~~~~~
The simulation script used for all the results gathered in this documentation is located at ``src/lte/examples/lena-runtime-profiler.cc``. This script generated a squared grid topology, placing a eNodeB at the centre of the square. UEs attached to this node are scattered randomly across the square (using a random uniform distribution along X and Y axis). If *BuildingPropagationModel* is used, the squares are replaced by rooms.
The simulation script used for all the E-UTRAN results showed in this documentation is located at ``src/lte/examples/lena-profiling.cc``. It uses the complete PHY and MAC UE/eNodeB implementation with a simplified RLC implementation on top. This script generates a squared grid topology, placing a eNodeB at the centre of each square. UEs attached to this node are scattered randomly across the square (using a random uniform distribution along X and Y axis). If *BuildingPropagationModel* is used, the squares are replaced by rooms. To generate the UL and DL traffic, the RLC implementation always report data to be transfered.
.. TODO: Insert figure picturing the geometry of the simulation.
.. _fig-eutranProfilingScenario:
RLC and MAC traces are enabled for all UEs and all eNodeBs and those traces are written to disk directly. The MAC scheduler used is *propotional fair*.
.. figure:: figures/eutran-profiling-scenario.*
:align: center
:width: 80%
E-UTRAN
For the EPC results, the script is ``src/lte/examples/lena-simple-epc.cc``. It uses a complete E-UTRAN implementation (PHY+MAC+RLC/UM+PDCP) and the most relevant EPC user plane entities the PGW and SGW, including GTP-U tunneling. This script generates a given number of eNodeBs, distributed across a line and attaches a single UE to every eNodeB. It also creates an EPC network and an external host connected to it through the Internet. Each UE sends and receives data to and from the remote host. In addition, each UE is also sending data to the UE camped in the adjacent eNodeB.
.. _fig-epcProfilingScenario:
.. figure:: figures/epc-profiling-scenario.*
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Propagation Model
RLC and MAC traces are enabled for all UEs and all eNodeBs and those traces are written to disk directly. The MAC scheduler used is *round robin*.
Simulation input parameters
---------------------------
The *lena-runtime-profiler* simulation script accepts the following input parameters:
The *lena-profiling* simulation script accepts the following input parameters:
* ``simTime``: time to simulate (in seconds)
* ``nUe``: number of UEs attached to each eNodeB
* ``nEnb``: number of eNodeB composing the grid per floor
* ``nFloors``: number of floors, 0 for *Friis propagation model* (no walls), 1 for *Building propagation model*
* ``nFloors``: number of floors, 0 for *Friis propagation model* (no walls), 1 or greater for *Building propagation model* generating a nFloors-storey building.
* ``traceDirectory``: destination directory where simulation traces will be stored
The *lena-simple-epc* script accepts those other parameters:
* ``simTime``: time to simulate (in seconds)
* ``numberOfNodes``: number of eNodeB + UE pairs created
Time measurement
~~~~~~~~~~~~~~~~
@@ -43,7 +63,7 @@ Running time is measured using default Linux shell command **time**. This comman
Perl script
~~~~~~~~~~~
To simplify the process of running the profiling script for a wide range of values and collecting its timing data, a simple Perl script to automate the complete process is provided. It is placed in ``src/lte/test/lte-test-run-time.pl``. It simply runs a batch of simulations with a range of parameters and stores the timing results in a CSV file called *times.csv*. The range of values each parameter takes can be easily modified editing the script.
To simplify the process of running the profiling script for a wide range of values and collecting its timing data, a simple Perl script to automate the complete process is provided. It is placed in ``src/lte/test/lte-test-run-time.pl`` for *lena-profiling* and in ``src/lte/epc-test-run-time.pl`` for *lena-simple-epc*. It simply runs a batch of simulations with a range of parameters and stores the timing results in a CSV file called *times.csv* and *epcTimes.csv* respectively. The range of values each parameter sweeps can be modified editing the corresponding script.
Requirements
------------
@@ -60,61 +80,63 @@ All timing tests had been run in a Intel Pentium IV 3.00 GHz machine with 512 Mb
Also, as a reference configuration, the build has been configured static and optimized. The exact ``waf`` command issued is:
``CXXFLAGS="-O3 -w" ./waf -d optimized configure --enable-static --enable-examples``
``CXXFLAGS="-O3 -w" ./waf -d optimized configure --enable-static --enable-examples --enable-modules=lte``
Results
*******
The following results and figures had been obtained with LENA **changeset 1823cde6f40b**.
E-UTRAN
~~~~~~~
The following results and figures had been obtained with LENA **changeset 2c5b0d697717**.
Running time
~~~~~~~~~~~~
------------
This scenario, evaluates the running time in for a fixed simulation time (10s) and Friis propagation mode increasing the number of UEs attached to each eNodeB and the number of planted eNodeBs in every scenario.
This scenario, evaluates the running time for a fixed simulation time (10s) and Friis propagation mode increasing the number of UEs attached to each eNodeB and the number of planted eNodeBs in the scenario.
.. _fig-runTime:
.. figure:: figures/runningTime10s.*
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Running time
The figure shows the expected behaviour, since it increases linearly respect the number of UEs per eNodeB and quadratically respect the total number of eNodeBs.
Propagation model
~~~~~~~~~~~~~~~~~
-----------------
The objective of this scenario is to evaluate the impact of the more complex building propagation model, so a set of scenarios has been run with Friis propagation model and Building propagation model and its run time are compared in the following figure.
The objective of this scenario is to evaluate the impact of the propagation model complexity in the overall run time figures. Therefore, the same scenario is simulated twice: once using the more simple Friis model, once with the more complex Building model. The rest of the parameters (e.g. number of eNodeB and of UE attached per eNodeB) were mantained. The timing results for both models are compared in the following figure.
.. _fig-runTime:
.. _fig-propagationModel:
.. figure:: figures/propagationModel.*
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Propagation Model
In this situation, results are also coherent with what is expected. The more complex the model, the higher the running time. Moreover, as the number of computed path losses increases (i.e. more UEs per eNodeB or more eNodeBs) the extra complexity of the propagation model drives the running time figures further apart.
Simulation time
~~~~~~~~~~~~~~~
---------------
In this scenario, for a fixed set of UEs per eNodeB, different simulation times had been run. As the simulation time increases, running time should also increase linearly. The slope of this line is a function of the complexity of the scenario: the more eNodeB / UEs placed, the higher the slope of the line.
In this scenario, for a fixed set of UEs per eNodeB, different simulation times had been run. As the simulation time increases, running time should also increase linearly, i.e. for a given scenario, simulate four seconds should take twice times what it takes to simulate two seconds. The slope of this line is a function of the complexity of the scenario: the more eNodeB / UEs placed, the higher the slope of the line.
.. _fig-runTime:
.. _fig-simulationTime:
.. figure:: figures/simulationTime.*
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Simulation time
Memory usage
~~~~~~~~~~~~
------------
Massif tool to profile memory consumption
@@ -122,7 +144,51 @@ Massif tool to profile memory consumption
.. figure:: figures/profiling-memory.*
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Memory profile
EPC
~~~
The following results and figures had been obtained with LENA **changeset e8b3ccdf6673**. The rationale behind the two scenarios profiled on this section is the same than for the E-UTRA part.
Running time
------------
Running time evolution is quadratic since we increase at the same time the number of eNodeB and the number of UEs.
.. _fig-epcRunTime:
.. figure:: figures/epcRunningTime.*
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Running time
As a rough complexity estimation, we compare two scenarios using the simplified E-UTRAN version (PHY+MAC) against the complete E-UTRAN + EPC, with same number of UEs per eNodeB, same number of eNodeBs and roughly same volume of transmitted data.
.. _fig-epcEutranRunTime:
.. figure:: figures/epcEutranRunningTime.*
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EPC E-UTRAN running time
Figures for the complete system are more or less doubling the previous one, but considering the overhead of all the logic and entities incorporated this order of increment is to be expected.
Simulation time
---------------
Finally, again the linearity of the running time as the simulation time increases gets validated through a set of experiments, as the following figure shows.
.. _fig-epcSimTime:
.. figure:: figures/epcSimulationTime.*
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Simulation time