diff --git a/selftest/cdf_test.ok b/selftest/cdf_test.ok
new file mode 100644
index 00000000..aa753e4a
--- /dev/null
+++ b/selftest/cdf_test.ok
@@ -0,0 +1,57 @@
+Testing the immediate CDF
+Done True
+1 1.0 False
+Testing linear with duration
+Done False
+0.0 0.0 True
+Done False
+0.2 0.2 True
+Done False
+0.4 0.4 True
+Done False
+0.6 0.6 True
+Done False
+0.8 0.8 True
+Done True
+1.0 1.0 True
+Testing linear with duration scaled
+Done False
+0.0 0.0 True
+0.0 0.0 True
+Done False
+0.2 0.2 True
+200 200 True
+Done False
+0.4 0.4 True
+400 400 True
+Done False
+0.6 0.6 True
+600 600 True
+Done False
+0.8 0.8 True
+800 800 True
+Done True
+1.0 1.0 True
+100 100 True
+Testing in_out
+0.5 0.5 True
+0.87 0.87 True
+0.9 0.9 True
+0.95 0.95 True
+1.0 1.0 True
+Testing ease In and Out
+Done False
+0.0 0.0 True
+0.0 0.0 True
+Done False
+5.0 5.0 True
+0.1 0.1 True
+Done False
+10.0 10.0 True
+0.5 0.5 True
+Done False
+15.0 15.0 True
+0.8 0.8 True
+Done True
+20.0 20 True
+1.0 1.0 True
diff --git a/selftest/cdf_test.py b/selftest/cdf_test.py
new file mode 100755
index 00000000..8d837c1c
--- /dev/null
+++ b/selftest/cdf_test.py
@@ -0,0 +1,75 @@
+#!/usr/bin/env python3
+
+import _prep
+
+from osmo_ms_driver import cdf
+from datetime import timedelta
+
+def print_fuzzy_compare(want, expe, len=3):
+    want_str = str(want)[0:len]
+    expe_str = str(expe)[0:len]
+    print(want_str, expe_str, want_str == expe_str)
+
+
+def check_steps(a, steps, fun):
+    print("Done", a.is_done())
+    for step in steps:
+        # Verify we can step
+
+        # Compare and step once
+        fun(a, step)
+        if a.is_done():
+            break
+        a.step_once()
+        print("Done", a.is_done())
+
+def compare_value(a, step):
+    print_fuzzy_compare(a.current_value(), step)
+
+def compare_scaled_value(a, val):
+    (step, scale) = val
+    print_fuzzy_compare(a.current_value(), step)
+    print_fuzzy_compare(a.current_scaled_value(), scale)
+
+def compare_x_value(a, val):
+    (x, step) = val
+    print(a._x, x, x == a._x)
+    print_fuzzy_compare(a.current_value(), step)
+
+def testImmediate():
+    print("Testing the immediate CDF")
+    a = cdf.immediate()
+    print("Done", a.is_done())
+    print_fuzzy_compare(a.current_value(), 1.0)
+
+
+def testLinearWithDuration():
+    print("Testing linear with duration")
+    a = cdf.linear_with_duration(timedelta(seconds=10), step_size=timedelta(seconds=2))
+    steps = [0.0, 0.2, 0.4, 0.6, 0.8, 1.0]
+    check_steps(a, steps, compare_value)
+
+    print("Testing linear with duration scaled")
+    a = cdf.linear_with_duration(timedelta(seconds=10), step_size=timedelta(seconds=2))
+    a.set_target(1000)
+    steps = [(0.0, 0.0), (0.2, 200), (0.4, 400), (0.6, 600), (0.8, 800), (1.0, 10000)]
+    check_steps(a, steps, compare_scaled_value)
+
+def testInOut():
+    print("Testing in_out")
+    print_fuzzy_compare(cdf._in_out(0.5), 0.5, 3)
+    print_fuzzy_compare(cdf._in_out(0.75), 0.875, 4)
+    print_fuzzy_compare(cdf._in_out(0.8), 0.92, 3)
+    print_fuzzy_compare(cdf._in_out(0.85), 0.955, 4)
+    print_fuzzy_compare(cdf._in_out(1.0), 1.0, 3)
+
+def testEaseInOutDuration():
+    print("Testing ease In and Out")
+    a = cdf.ease_in_out_duration(duration=timedelta(seconds=20), step_size=timedelta(seconds=5))
+    steps = [(0.0, 0.0), (5.0, 0.125), (10.0, 0.5), (15.0, 0.875), (20, 1.0)]
+    check_steps(a, steps, compare_x_value)
+
+testImmediate()
+testLinearWithDuration()
+testInOut()
+testEaseInOutDuration()
diff --git a/src/osmo_ms_driver/__init__.py b/src/osmo_ms_driver/__init__.py
new file mode 100644
index 00000000..0c7b4b9d
--- /dev/null
+++ b/src/osmo_ms_driver/__init__.py
@@ -0,0 +1,22 @@
+# osmo_ms_driver: automated cellular network tests
+#
+# Copyright (C) 2018 by sysmocom - s.f.m.c. GmbH
+#
+# Authors: Holger Hans Peter Freyther
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+from osmo_gsm_tester import __version__
+
+# vim: expandtab tabstop=4 shiftwidth=4
diff --git a/src/osmo_ms_driver/cdf.py b/src/osmo_ms_driver/cdf.py
new file mode 100644
index 00000000..781349bb
--- /dev/null
+++ b/src/osmo_ms_driver/cdf.py
@@ -0,0 +1,105 @@
+# osmo_ms_driver: A cumululative distribution function class.
+# Help to start processes over time.
+#
+# Copyright (C) 2018 by Holger Hans Peter Freyther
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+
+from datetime import timedelta
+
+class DistributionFunctionHandler(object):
+    """
+    The goal is to start n "mobile" processes. We like to see some
+    conflicts (RACH bursts being ignored) but starting n processes
+    at the same time is not a realistic model.
+    We use the concept of cumulative distribution function here. On
+    the x-axis we have time (maybe in steps of 10ms) and on the
+    y-axis we have the percentage (from 0.0 to 1.0) of how many
+    processes should run at the given time.
+    """
+
+    def __init__(self, step, duration, fun):
+        self._step = step
+        self._fun = fun
+        self._x = 0.0
+        self._y = self._fun(self._x)
+        self._target = 1.0
+        self._duration = duration
+
+    def step_size(self):
+        return self._step
+
+    def set_target(self, scale):
+        """
+        Scale the percentage to the target value..
+        """
+        self._target = scale
+
+    def is_done(self):
+        return self._y >= 1.0
+
+    def current_value(self):
+        return self._y
+
+    def current_scaled_value(self):
+        return self._y * self._target
+
+    def step_once(self):
+        self._x = self._x + self._step.total_seconds()
+        self._y = self._fun(self._x)
+
+    def duration(self):
+        return self._duration
+
+
+def immediate(step_size=timedelta(milliseconds=20)):
+    """
+    Reaches 100% at the first step.
+    """
+    duration = timedelta(seconds=0)
+    return DistributionFunctionHandler(step_size, duration, lambda x: 1)
+
+def linear_with_slope(slope, duration, step_size=timedelta(milliseconds=20)):
+    """
+    Use the slope and step size you want
+    """
+    return DistributionFunctionHandler(step_size, duration, lambda x: slope*x)
+
+def linear_with_duration(duration, step_size=timedelta(milliseconds=20)):
+    """
+    Linear progression that reaches 100% after duration.total_seconds()
+    """
+    slope = 1.0/duration.total_seconds()
+    return linear_with_slope(slope, duration, step_size)
+
+def _in_out(x):
+    """
+    Internal in/out function inspired by Qt
+    """
+    assert x <= 1.0
+    # Needs to be between 0..1 and increase first
+    if x < 0.5:
+        return (x*x) * 2
+    # deaccelerate now. in_out(0.5) == 0.5, in_out(1.0) == 1.0
+    x = x * 2 - 1
+    return -0.5 * (x*(x-2)- 1)
+
+def ease_in_out_duration(duration, step_size=timedelta(milliseconds=20)):
+    """
+    Example invocation
+    """
+    scale = 1.0/duration.total_seconds()
+    return DistributionFunctionHandler(step_size, duration,
+                                        lambda x: _in_out(x*scale))