import os
logging.config.fileConfig('/home/thiago/YAFS/src/examples/Tutorial/logging.ini')
start_time = time.time()
# duracao a simulacao
simulated_time = 100
main(simulated_time=simulated_time)
print("\n--- %s seconds ---" % (time.time() - start_time))
### Finally, you can analyse the results:
print "-"*20
print "Results:"
print "-" * 20
m = Stats(defaultPath="Results") #Same name of the results
time_loops = [["M.Cam1","M.MLT", "M.FLT"]]
# TODO: COLOCAR AS OUTRAS MENSAGENS EM time_loops
m.showResults2(simulated_time, time_loops=time_loops)
m.df["date"] = m.df.time_in.astype('datetime64[s]')
m.df.index = m.df.date
print "Media da latencia a cada 10 segundos"
print m.df.resample('10s').agg(dict(time_latency='mean'))
print "\t- Network saturation -"
print "\t\tAverage waiting messages : %i" % m.average_messages_not_transmitted()
print "\t\tPeak of waiting messages : %i" % m.peak_messages_not_transmitted()
print "\t\tTOTAL messages not transmitted: %i" % m.messages_not_transmitted()
# print "\n\t- Stats of each service deployed -"
# print m.get_df_modules()
'module': False,
'time': 9700
}, {
'id': 56,
'module': False,
'time': 9800
}, {
'id': 290,
'module': False,
'time': 9900
}]
print "Number of nodes removed: ", len(failures)
# Basic analysis
time_loops = [["M.Action"]]
s = Stats(defaultPath=path + "Results_%s_exp" % (size))
s.showResults2(size, time_loops=time_loops)
# Visualization of latency time series:
dfail = pd.DataFrame.from_dict(failures)
dfail["date"] = dfail.time.astype('datetime64[s]')
dfail.index = dfail.date
dfail['module'] = dfail.module.astype(str)
dfail = dfail.resample('10s').agg(
{"module": "-".join}) #OPTIONAL BE CAREFOUL: resampling -> agg events
#dict(module=''))['module'].apply(list)
df = s.df
dfl = s.df_link
if __name__ == '__main__':
import logging.config
import os
logging.config.fileConfig(os.getcwd() + '/logging.ini')
start_time = time.time()
main(simulated_time=1000)
print("\n--- %s seconds ---" % (time.time() - start_time))
### Finally, you can analyse the results:
print "-" * 20
print "Results:"
print "-" * 20
m = Stats(defaultPath="Results_multiple") #Same name of the results
time_loops = [["M.A", "M.B"]]
m.showResults2(1000, time_loops=time_loops)
print "\t- Network saturation -"
print "\t\tAverage waiting messages : %i" % m.average_messages_not_transmitted(
)
print "\t\tPeak of waiting messages : %i" % m.peak_messages_not_transmitted(
)
print "\t\tTOTAL messages not transmitted: %i" % m.messages_not_transmitted(
)
print "\n\t- Stats of each service deployed -"
print m.get_df_modules()
print m.get_df_service_utilization("ServiceA", 1000)
print "\n\t- Stats of each DEVICE -"
time_loops = [["M.EGG", "M.Sensor", "M.Concentration"]]
#### ANALYSE FILES YAFS
police = "cloud"
police = "edge"
# print depth
# for idx1, depth in enumerate([4, 8, 12, 16]):
for idx1, depth in enumerate([2]):
# 1000, 10000,
for idx2,size in enumerate([1000,10000,100000]):
# size = 100000
print "DEPTH: %i | TIME: %s" %(depth , size)
s = Stats(defaultPath="Results_%s_%s_%s"%(police,size,depth))
#Network
s.showResults2(size, time_loops=time_loops)
print "\t Bytes transmitted: " ,s.bytes_transmitted()
print "\t Messages transmitted: ",s.count_messages()
print "\t- Network saturation -"
print "\t\tAverage waiting messages : %i" % s.average_messages_not_transmitted()
print "\t\tPeak of waiting messages : %i" % s.peak_messages_not_transmitted()
print "\t\tTOTAL messages not transmitted: %i" % s.messages_not_transmitted()
#LOOPS
# res = s.showLoops(time_loops)
# loopstime[depth][idx2]=res[0]
from pandas import Series, date_range
from matplotlib.ticker import FormatStrFormatter
# for size in [100,1000,10000,100000,1000000]:
time_loops = [["M.Action"]]
#### ANALYSE FILES YAFS
app1 = "app1"
app2 = "app2"
size = 12000
path = "examples/DynamicAllocation/"
#s = Stats(defaultPath=path+"Results_%s"%(size))
s1 = Stats(defaultPath=path + "Results_%s_singleApp1" % (size))
#s2 = Stats(defaultPath=path+"Results_%s_singleApp2" % (size))
#Network
#s.showResults2(size, time_loops=time_loops)
#app1 based on dinamic Edge
s1.showResults2(size, time_loops=time_loops)
#app2 based on static Cloud
#s2.showResults2(size, time_loops=time_loops)
df = s1.df
dfl = s1.df_link
#df["date"]=df.time_in.astype('timedelta64[s]')
df["date"] = df.time_in.astype('datetime64[s]')
df.index = df.date
s.run(stop_time, show_progress_monitor=False)
# s.draw_allocated_topology() # for debugging
if __name__ == '__main__':
import logging.config
import os
logging.config.fileConfig(os.getcwd() + '/logging.ini')
start_time = time.time()
main(simulated_time=1000)
print("\n--- %s seconds ---" % (time.time() - start_time))
### Finally, you can analyse the results:
print "-" * 20
print "Results:"
print "-" * 20
m = Stats(defaultPath="Results") #Same name of the results
time_loops = [["M.A", "M.B"]]
m.showResults2(1000, time_loops=time_loops)
print "\t- Network saturation -"
print "\t\tAverage waiting messages : %i" % m.average_messages_not_transmitted(
)
print "\t\tPeak of waiting messages : %i" % m.peak_messages_not_transmitted(
)
print "\t\tTOTAL messages not transmitted: %i" % m.messages_not_transmitted(
)