def iso_map_dynamic(current_value_list, label, transition, closest_monitor_range, action_status):
dynamic_all_values.append(current_value_list)
write_as_template(dynamic_all_values, violation_position)
if(len(dynamic_all_values) > 12):
X = numpy.array(dynamic_all_values)
# print "Actual Values: ",X
#For all the dimensions normalise the value range between 0 and 1
#use ceiling function to remove small noise
X = util.scale(X)
util.compute_utilization(util.scale_list(current_value_list))
#n_neighbors = 10
#Y = manifold.Isomap(n_neighbors, 2, max_iter= 4000).fit_transform(X)
Y = manifold.MDS().fit_transform(X)
#Y = manifold.LocallyLinearEmbedding().fit_transform(X)
old_values = Y[:-1]
new_value = Y[-1:]
plot.animated_plot(old_values, new_value, violation_position, action_status)
if closest_monitor_range:
closest_range_position.append(len(dynamic_all_values) -1)
# If transition, remove all the values until the closest_range_position
# remove matching violation_position. It is important to do this before violation position is included inorder to feed in the updated (correct)
# position of dynamic_values to violation_position.
if transition:
# print "!!!!!!!!!!Transition detected!!!!!!!!!! "
# print "Closest Range positions (before): " ,closest_range_position
# print "Violation positions (before) ", violation_position
# print "Length All Values (before): ", len(dynamic_all_values)
# reversed is important. Remove elements at the end first to avoid messing up index in subsequent deletions.
if len(closest_range_position) >1:
for position in reversed(xrange(closest_range_position[-2]+1, closest_range_position[-1])):
print "Deleting element in position: ", position
del dynamic_all_values[position]
if position in violation_position:
violation_position.remove(position)
#closest_Range_position[-1] does not anymore hold the right position. update the position by number of elements deleted.
closest_range_position[-1] = closest_range_position[-1] - abs(closest_range_position[-2]+1 - closest_range_position[-1])
# print "Length All Values (after): ", len(dynamic_all_values)
# print "Violation positions (after) ", violation_position
# print "Closest Range positions (after): " ,closest_range_position
# Append the position of the violation only after plotting
# inorder to plot the current value as current point instead of a violation
if label:
violation_position.append(len(dynamic_all_values)-1)
def monitorStore(processing_time):
"""
Get monitored information
find timestamp
read violation-file
if violation happened in the last period, attach violation label
send to mds
"""
# commented to use psutil system info system_info = systeminfo.get_all_info()
global previous_scaled_monitored_list
global previous_violation_label
global learn_distance
system_info = {}
violation_label = False
transition = False
closest_monitor_range = False
application_timestamp = None
qos_metric = None
monitored_timestamp = util.get_current_system_timestamp()
info_dict, current_monitored_list = sliverinfo.collectAllData()
system_info.update(info_dict)
file_values = read_violation_file()
if file_values and len(file_values) ==2 :
application_timestamp, qos_metric = file_values
print "Total no. of Frames Encoded: ", qos_metric
# print "Monitored Timestamp: ", monitored_timestamp
# print "QoS Metric Timestamp: ", application_timestamp
#Check if the current value falls within the range of monitor. The closest_monitor_range is the first
# monitored value closest to the application timestamp
if application_timestamp and abs(application_timestamp - monitored_timestamp) < config.TIMEPERIOD + processing_time :
closest_monitor_range = True
if qos_metric:
if config.latency_app is not 'vlc':
violation_label = check_violation(qos_metric)
else:
violation_label = vlc.qos.check_violation(qos_metric, application_timestamp)
transition = check_transition(violation_label)
# If an action has been taken, compare the measurement vectors to decide when to revoke the action
if action_status:
scaled_monitored_list = util.scale_list(current_monitored_list)
if previous_scaled_monitored_list:
dist = distance.calculate_distance_list(scaled_monitored_list, previous_scaled_monitored_list)
print "Distance: ", dist
if dist and dist > learn_distance:
#revoke action and reset previous_monitored_list to None to start afresh
revoke_action()
previous_scaled_monitored_list = None
else:
previous_scaled_monitored_list = scaled_monitored_list
#Transition check over. Safe to update previous violation label.
if violation_label:
previous_violation_label= True
print "HIT!!! Label as Violation"
# Pause the batch application.
take_action()
else:
previous_violation_label = False
mds.iso_map_dynamic(current_monitored_list, violation_label, transition, closest_monitor_range, action_status)
end_timestamp = util.get_current_system_timestamp()
processing_time = end_timestamp - monitored_timestamp
#print "Processing Time: ", processing_time
return processing_time
