x/terracotta
Code Issues Proposed changes

Added a new underload detection algorithm: last_n_average_threshold

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This commit is contained in:
Anton Beloglazov 2012-10-30 10:01:04 +11:00
parent df55d8b401
commit 5a924db694
2 changed files with 92 additions and 0 deletions
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47
neat/locals/underload/trivial.py
View File

@ -42,6 +42,28 @@ def threshold_factory(time_step, migration_time, params):
utilization),
{})
@contract
def last_n_average_threshold_factory(time_step, migration_time, params):
""" Creates the averaging threshold underload detection algorithm.
:param time_step: The length of the simulation time step in seconds.
:type time_step: int,>=0
:param migration_time: The VM migration time in time seconds.
:type migration_time: float,>=0
:param params: A dictionary containing the algorithm's parameters.
:type params: dict(str: *)
:return: A function implementing the OTF algorithm.
:rtype: function
"""
return lambda utilization, state=None: (
last_n_average_threshold(params['threshold'],
params['n'],
utilization),
{})
@contract
def threshold(threshold, utilization):
@ -62,3 +84,28 @@ def threshold(threshold, utilization):
if utilization:
return utilization[-1] <= threshold
return False
@contract
def last_n_average_threshold(threshold, n, utilization):
""" Averaging static threshold-based underload detection algorithm.
The algorithm returns True, if the average of the last n values of
the host's CPU utilization is lower than the specified threshold.
:param threshold: The static underload CPU utilization threshold.
:type threshold: float,>=0,<=1
:param n: The number of last values to average.
:type n: int,>0
:param utilization: The history of the host's CPU utilization.
:type utilization: list(float)
:return: A decision of whether the host is underloaded.
:rtype: bool
"""
if utilization:
utilization = utilization[-n:]
return sum(utilization) / len(utilization) <= threshold
return False

45
tests/locals/underload/test_trivial.py
View File

@ -32,6 +32,27 @@ class Trivial(TestCase):
self.assertEqual(alg([0.0, 0.6]), (False, {}))
self.assertEqual(alg([0.0, 1.0]), (False, {}))
def test_last_n_average_threshold_factory(self):
alg = trivial.last_n_average_threshold_factory(
300, 20., {'threshold': 0.5,
'n': 2})
self.assertEqual(alg([]), (False, {}))
self.assertEqual(alg([0.0, 0.0]), (True, {}))
self.assertEqual(alg([0.0, 0.4]), (True, {}))
self.assertEqual(alg([0.0, 0.5]), (True, {}))
self.assertEqual(alg([0.0, 0.6]), (True, {}))
self.assertEqual(alg([0.0, 1.0]), (True, {}))
self.assertEqual(alg([0.2, 1.0]), (False, {}))
self.assertEqual(alg([0.0, 0.2, 1.0]), (False, {}))
self.assertEqual(alg([0.0, 1.0, 1.0]), (False, {}))
self.assertEqual(alg([0.0, 0.6, 0.6]), (False, {}))
alg = trivial.last_n_average_threshold_factory(
300, 20., {'threshold': 0.5,
'n': 3})
self.assertEqual(alg([0.0, 0.6, 0.6]), (True, {}))
def test_threshold(self):
self.assertEqual(trivial.threshold(0.5, []), False)
self.assertEqual(trivial.threshold(0.5, [0.0, 0.0]), True)
@ -39,3 +60,27 @@ class Trivial(TestCase):
self.assertEqual(trivial.threshold(0.5, [0.0, 0.5]), True)
self.assertEqual(trivial.threshold(0.5, [0.0, 0.6]), False)
self.assertEqual(trivial.threshold(0.5, [0.0, 1.0]), False)
def test_last_n_average_threshold(self):
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, []), False)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 0.0]), True)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 0.4]), True)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 0.5]), True)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 0.6]), True)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 1.0]), True)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.2, 1.0]), False)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 0.2, 1.0]), False)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 1.0, 1.0]), False)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 2, [0.0, 0.6, 0.6]), False)
self.assertEqual(trivial.last_n_average_threshold(
0.5, 3, [0.0, 0.6, 0.6]), True)