def analyzePacket(simulation_time, incoming_packet, threshold, user_list, users, encounters):
source = incoming_packet[0]
destination = incoming_packet[1]
asker = incoming_packet[2]
expert = incoming_packet[3]
ttl = incoming_packet[4]
question = incoming_packet[5]
answer = incoming_packet[6]
tags = incoming_packet[7]
confidence = incoming_packet[8]
ev_asker = incoming_packet[9]
ev_expert = incoming_packet[10]
this_user = user_list[users.index(destination)]
if ttl < 1:
# drop packet if it has expired
this_user.remove_from_buffer(incoming_packet)
if answer == 0:
msg = question
else:
msg = answer
return (-1, -1, msg)
if this_user.user_id == asker:
# dynamic tagging initiation phase
if trust.enough_confidence(confidence, threshold) == 1:
# if participating users are confident of expert
# send expert's response (answer) offline to
# storage where it will be clustered along
# other expert responses and displayed on
# user's screen asynchronously (not in simulation)
this_user.add_expert_to_response(expert, ev_expert, question, answer)
if answer == 0:
msg = question
else:
msg = answer
# drop packet
this_user.remove_from_buffer(incoming_packet)
if answer == 0:
msg = question
else:
msg = answer
return (source, destination, msg)
if expert == 0:
# broadcast message: looking for experts!
# query creation and forwarding phase
owner_response = ui.display_user(this_user, tags, question)
# owner_response: {yes/no, {{tag, location}...}, answer, ev_thisNode}
if owner_response[0] == 1:
# current node's device owner
# identifies him/herself as an expert
# send packet containing expert response to nbrs
response = 0
for encounter in encounters:
if encounter[1] not in users:
continue
if encounter[2] == simulation_time:
if encounter[0] == this_user.user_id:
response = response + 1
# send response to nbr
this_packet = (this_user.user_id, encounter[1], asker, this_user.user_id,\
out_ttl, question, owner_response[2],\
owner_response[1],\
[0 for i in range(len(owner_response[1]))],\
ev_asker,\
owner_response[3])
user_list[users.index(encounter[1])].\
add_to_buffer(this_packet)
if response > response_threshold:
this_user.remove_from_buffer(incoming_packet)
# keep message in buffer
if answer == 0:
msg = question
else:
msg = answer
return (source, destination, msg)
else:
# no response from owner just forward packet
response = 0
# epidemic flooding
for encounter in encounters:
if encounter[1] not in users:
continue
if encounter[2] == simulation_time:
if encounter[0] == this_user.user_id:
response = response + 1
this_packet = (this_user.user_id, encounter[1], asker, expert,\
ttl-1, question, answer, tags,\
confidence, ev_asker, [])
user_list[users.index(encounter[1])].\
add_to_buffer(this_packet)
if response > response_threshold:
this_user.remove_from_buffer(incoming_packet)
if answer == 0:
msg = question
else:
msg = answer
return (source, destination, msg)
else:
# expert identification phase
# message is being sent by self-identified
# ...expert to asker
if this_user.user_id == expert:
this_user.remove_from_buffer(incoming_packet)
if answer == 0:
msg = question
else:
msg = answer
return (-1, -1, msg)
else:
# scoped routing/gradient descent:
if trust.enough_confidence(confidence, threshold) == 1:
# enough confidence votes (negative/positive)
# have been obtained. Send packet to users who mobility
# matches Asker
# confidence is high but drop packet current user is not similar
# to asker
if this_user.is_similar(ev_asker, threshold) == 0:
# asker is not similar to me
# drop packet
this_user.remove_from_buffer(incoming_packet)
color = 'red'
return (source, destination, color)
response = 0
for encounter in encounters:
if encounter[1] not in users:
continue
if encounter[2] == simulation_time:
if encounter[0] == this_user.user_id:
response = response + 1
this_packet = (this_user.user_id, encounter[1], asker, expert,\
ttl-1, question, answer, tags,\
confidence, ev_asker, ev_expert)
user_list[users.index(encounter[1])].\
add_to_buffer(this_packet)
if response > response_threshold:
this_user.remove_from_buffer(incoming_packet)
elif trust.enough_confidence(confidence, threshold) == -1:
# bad response
# drop packet
this_user.remove_from_buffer(incoming_packet)
else:
# need to forward the packet to users whose mobility
# matches expert to obtain more votes
for i in range(len(tags)):
seen_before = this_user.has_seen(expert, tags[i], threshold)
if seen_before == 1:
# this node visits tag,location frequently
# ...and has seen expert
confidence[i] = confidence[i] + 1
elif seen_before == -1:
# this node visits tag,location frequently
# ...and has NOT seen expert
confidence[i] = confidence[i] - 1
response = 0
for encounter in encounters:
if encounter[1] not in users:
continue
if encounter[2] == simulation_time:
if encounter[0] == this_user.user_id:
response = response + 1
this_packet = (this_user.user_id, encounter[1], asker, expert,\
ttl-1, question, answer, tags,\
confidence, ev_asker, [])
user_list[users.index(encounter[1])].\
add_to_buffer(this_packet)
if response > response_threshold:
this_user.remove_from_buffer(incoming_packet)
if answer == 0:
msg = question
else:
msg = answer
return (source, destination, msg)
# if len(user.answer_folder) > 0:
# print user.answer_folder
# print "\n"
o.write("nx.draw_random(G)\n")
o.write("plt.savefig('path_"+str(time_unit)+".png')")
o.close()
for user in user_list:
print user.user_id, str(len(user.input_msg_buffer))
print "\n\nQuestion asked: '" + question_tag[0] + "' by Asker: " + str(asker)
if len(user_list[users.index(asker)].answer_folder) > 0:
print 'Simulation successful.'
for msg in user_list[users.index(asker)].answer_folder:
print "Answer: '" + msg[2] + "' by Expert: " + str(msg[0])
else:
bad_replies = []
if len(user_list[users.index(asker)].input_msg_buffer) > 0:
for msg in user_list[users.index(asker)].input_msg_buffer:
if msg[3] != 0:
if trust.enough_confidence(msg[8], 0) != 1:
# format: <expert_id, confidence, answer>
bad_replies.append((msg[3],msg[8],msg[6]))
if len(bad_replies) > 0:
print 'Received bad responses such as: Expert: '+\
str(bad_replies[0][0])+' Confidence Score: '+\
' '.join([str(reply) for reply in bad_replies[0][1]])+' Answer: '+bad_replies[0][2]
else:
print 'No bad responses'
