def pre_optimal_ass(pool_of_tasks, v, pos):
"""
生成pre_scheduling assignment
:param pool_of_tasks: 任务池
:param v:虚拟机列表
:return: pre_opt_ass
"""
pre_opt_ass = []
for l in range(10000):
if not pool_of_tasks.empty():
tl1 = pool_of_tasks.get()
# print(pool_of_tasks.empty(), len(tl1), tl1)
et1 = t.test_et(v, tl1, pos)
ass1, f1, delays1 = t.ass1(v, tl1, et1, pos)
pre_opt_ass += delays1
else:
break
if not pool_of_tasks.empty():
tl2 = pool_of_tasks.get()
# print (pool_of_tasks.empty (), len(tl2), tl2)
et2 = t.test_et(v, tl2, pos)
wl = t.rand_wl(v, tl2, 3, 6)
ass2, f2, delays2 = t.ass2(v, tl2, wl, et2, pos)
pre_opt_ass += delays2
else:
break
if not pool_of_tasks.empty():
tl3 = pool_of_tasks.get()
# print(pool_of_tasks.empty(), len(tl3), tl3)
et3 = t.test_et(v, tl3, pos)
unit_price = t.unit_price(v)
pt3 = t.rand_pt(v, tl3, et3, unit_price, pos)
ass3, f3, delays3 = t.ass3(v, tl3, et3, pt3, pos)
pre_opt_ass += delays3
else:
break
taskNum = len(pre_opt_ass)
gameSta = round(taskNum / 8)
print('预分配结束', taskNum, gameSta, pre_opt_ass)
return pre_opt_ass, taskNum, gameSta
exec_pro1 = [7.1, 5.8, 4.8]
exec_pro2 = [7.4, 6.2, 5.1]
exec_pro3 = [6.7, 5.5, 4.3]
exec_v = exec_pro1 + exec_pro2 + exec_pro3
pri_pro1 = [0.023, 0.0464, 0.0928]
pri_pro2 = [0.0246, 0.0493, 0.0739]
pri_pro3 = [0.1053, 0.1244, 0.1373]
price = pri_pro1 + pri_pro2 + pri_pro3
Tn = w1 + w2 + w3 + w4 + w5
Vn = p1 + p2 + p3
V = t.rand_v('v', Vn)
vm_price = t.unit_price(V)
task_pool = t.t_pool(Tn, 10000) # 层级上限是10000
print('round ' + pos)
pre_optimal_ass_fifoi, task_number, game_stage = pre_optimal_ass_fifo(
task_pool, V, pos)
use_submit(pre_optimal_ass_fifoi, V, pos)
# 后续采集task number, game stage, makespan, workload, profit数据
print('采集数据')
csv_file = '.\\datafile\\' + pos + '\\res.csv'
ass1_file = '.\\datafile\\' + pos + '\\ass1.in'
ass2_file = '.\\datafile\\' + pos + '\\ass2.in'
ass3_file = '.\\datafile\\' + pos + '\\ass3.in'
pid_nums = g.pid_num(csv_file)
task_nums = g.task_num(csv_file)
tasks = g.task(csv_file)