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"""
Generate random task sets for schedulability experiments.
"""
import re
import random
from functools import partial
import schedcat.generator.tasks as gen
def decode_params(name):
# uni-UMIN-UMAX-PMIN-PMAX
# bimo-
# exp-UMIN-UMAX-MEAN-PMIN-PMAX
pass
NAMED_PERIODS = {
# Named period distributions used in several UNC papers, in milliseconds.
'uni-short' : gen.uniform_int( 3, 33),
'uni-moderate' : gen.uniform_int(10, 100),
'uni-long' : gen.uniform_int(50, 250),
}
NAMED_UTILIZATIONS = {
# Named utilization distributions used in several UNC papers, in milliseconds.
'uni-light' : gen.uniform(0.001, 0.1),
'uni-medium' : gen.uniform(0.1 , 0.4),
'uni-heavy' : gen.uniform(0.5 , 0.9),
'exp-light' : gen.exponential(0, 1, 0.10),
'exp-medium' : gen.exponential(0, 1, 0.25),
'exp-heavy' : gen.exponential(0, 1, 0.50),
'bimo-light' : gen.multimodal([(gen.uniform(0.001, 0.5), 8),
(gen.uniform(0.5 , 0.9), 1)]),
'bimo-medium' : gen.multimodal([(gen.uniform(0.001, 0.5), 6),
(gen.uniform(0.5 , 0.9), 3)]),
'bimo-heavy' : gen.multimodal([(gen.uniform(0.001, 0.5), 4),
(gen.uniform(0.5 , 0.9), 5)]),
}
def uniform_slack(min_slack_ratio, max_slack_ratio):
"""Choose deadlines uniformly such that the slack
is within [cost + min_slack_ratio * (period - cost),
cost + max_slack_ratio * (period - cost)].
Setting max_slack_ratio = 1 implies constrained deadlines.
"""
def choose_deadline(cost, period):
slack = period - cost
earliest = slack * min_slack_ratio
latest = slack * max_slack_ratio
return cost + random.uniform(earliest, latest)
return choose_deadline
NAMED_DEADLINES = {
'implicit' : None,
'uni-constrained' : uniform_slack(0, 1),
'uni-arbitrary' : uniform_slack(0, 2),
}
def mkgen(utils, periods, deadlines=None):
if deadlines is None:
g = gen.TaskGenerator(periods, utils)
else:
g = gen.TaskGenerator(periods, utils, deadlines)
return partial(g.make_task_set)
def make_standard_dists(dl='implicit'):
by_period = {}
for p in NAMED_PERIODS:
by_util = {}
by_period[p] = by_util
for u in NAMED_UTILIZATIONS:
by_util[u] = mkgen(NAMED_UTILIZATIONS[u],
NAMED_PERIODS[p],
NAMED_DEADLINES[dl])
return by_period
# keyed by deadline type, then by period, then by utilization
DIST_BY_KEY = {}
for dl in NAMED_DEADLINES:
DIST_BY_KEY[dl] = make_standard_dists(dl)
ALL_DISTS = {}
for dl in NAMED_DEADLINES:
for p in NAMED_PERIODS:
for u in NAMED_UTILIZATIONS:
ALL_DISTS[':'.join([u, p, dl])] = DIST_BY_KEY[dl][p][u]
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