def run_general(scheme, trace, nflows, nruns, nlandmarks, scale_list,
percentage, num_max_cache):
assert (trace in VALID_TRACES)
assert (scheme in VALID_SCHEMES)
# initialize topology and transactions from the dataset
G_ori, trans = get_topology_and_transactions(trace)
# find the right threshold for the requested "percentage"
threshold = get_threshold(trace, trans, percentage)
# run simulation ("nruns" times) for every possible "scale_factor" value and record
# and average over success ratio, success volume, transaction fees,
# number of probing messages, and cache hit probability (Flash only)
res_ratio = []
res_volume = []
res_cost = []
res_msg = []
res_hit = []
for scale_factor in scale_list:
G = nx.DiGraph()
G = scale_topo_cap(G_ori, scale_factor)
volume_list = []
ratio_list = []
cost_list = []
msg_list = []
hit_list = []
print('Start run simulation for trace', trace, '- scheme', scheme,
'- scale factor', scale_factor)
# payments to send
for seed in range(nruns):
random.seed(seed)
payments = generate_payments(trace, seed, nflows, trans, G)
if scheme == 'sp':
volume, cost, num_delivered, total_probing_messages, total_max_path_length = shortest_path.routing(
G.copy(), payments)
elif scheme == 'speedymurmurs':
volume, cost, num_delivered, total_probing_messages, total_max_path_length = speedymurmurs.routing(
G.copy(), payments, nlandmarks)
elif scheme == 'waterfilling':
volume, cost, num_delivered, total_probing_messages, total_max_path_length = waterfilling.routing(
G.copy(), payments)
elif scheme == 'flash':
volume, cost, num_delivered, total_probing_messages, total_max_path_length, hit_ratio, table_size, micro_volume, micro_msg = flash.routing(
G.copy(), payments, threshold, num_max_cache)
# record stats for the current run
volume_list.append(1.0 * volume)
ratio_list.append(1.0 * num_delivered / nflows)
cost_list.append(cost)
msg_list.append(1.0 * total_probing_messages)
if scheme == 'flash':
hit_list.append(hit_ratio)
# average over runs and store averages
res_volume.append(sum(volume_list) / nruns)
res_ratio.append(sum(ratio_list) / nruns)
res_cost.append(sum(cost_list) / nruns)
res_msg.append(sum(msg_list) / nruns)
if scheme == 'flash':
res_hit.append(sum(hit_list) / nruns)
print(scheme, res_cost)
# log results to file
with open(f'{trace}-{scheme}-{nflows}.txt', 'w') as filehandle:
filehandle.write(' '.join([str(e) for e in res_volume]) + '\n')
filehandle.write(' '.join([str(e) for e in res_ratio]) + '\n')
filehandle.write(' '.join([str(e) for e in res_msg]) + '\n')
if scheme == 'flash':
filehandle.write(' '.join([str(e) for e in res_hit]) + '\n')
def run_flash_cache(trace, nflows, nruns, scale_factor, percentage,
cache_list):
assert (trace in VALID_TRACES)
# initialize topology and transactions from the dataset
G_ori, trans = get_topology_and_transactions(trace)
# run Flash simulation ("nruns" times) for every possible "num_max_cache" value and record
# and average over success ratio, success volume, and number of probing messages
flash_micro_volume = []
flash_micro_msg = []
flash_ratio = []
flash_hit = []
flash_table = []
for num_max_cache in cache_list:
G = scale_topo_cap(G_ori, scale_factor)
threshold = get_threshold(trace, trans, percentage)
micro_volume_list = []
micro_msg_list = []
ratio_list = []
hit_list = []
table_list = []
# payments to send
for seed in range(nruns):
print('Start run simulation. Run', seed)
payments = generate_payments(trace, seed, nflows, trans, G)
# todo: lightning trace??? (remark: seems that "flash_micro_msg" remains empty for "lightning"? at least that is the case in "sim/result/rawdata/lightning-cache.txt")
volume, cost, num_delivered, total_probing_messages, total_max_path_length, hit_ratio, table_size, micro_volume, micro_msg = flash.routing(
G.copy(), payments, threshold, num_max_cache)
# record stats for the current run
micro_volume_list.append(1.0 * micro_volume)
micro_msg_list.append(micro_msg)
ratio_list.append(1.0 * num_delivered / nflows)
hit_list.append(hit_ratio)
table_list.append(table_size)
# average over runs and store averages
flash_micro_volume.append(sum(micro_volume_list) / nruns)
flash_micro_msg.append(sum(micro_msg_list) / nruns)
flash_ratio.append(sum(ratio_list) / nruns)
flash_hit.append(sum(hit_list) / nruns)
flash_table.append(sum(table_list) / nruns)
# log results to file
with open(f'{trace}-cache.txt', 'w') as filehandle:
filehandle.write(' '.join([str(e) for e in flash_micro_volume]) + '\n')
filehandle.write(' '.join([str(e) for e in flash_ratio]) + '\n')
filehandle.write(' '.join([str(e) for e in flash_hit]) + '\n')
filehandle.write(' '.join([str(e) for e in flash_table]) + '\n')
filehandle.write(' '.join([str(e) for e in flash_micro_msg]) + '\n')
def run_flash_cache(trace, nflows, nruns, scale_factor, percentage, cache_list):
G_ori = nx.DiGraph()
trans = []
if (trace == 'ripple'):
G_ori, trans = ripple_proc.setup()
if (trace == 'lightning'):
G_ori, trans = lightning_proc.setup()
flash_micro_volume = []
flash_micro_msg = []
flash_ratio = []
flash_hit = []
flash_table = []
for num_max_cache in cache_list:
G = scale_topo_cap(G_ori, scale_factor)
threshold = get_threshold(trace, trans, percentage)
micro_volume_list = []
micro_msg_list = []
ratio_list = []
hit_list = []
table_list = []
# payments to send
for seed in range(nruns):
print 'Start run simulation. Run', seed
payments = []
if trace == 'ripple':
payments = ripple_proc.generate_payments(seed, nflows, trans, G)
if trace == 'lightning':
payments = lightning_proc.generate_payments(seed, nflows, trans, G)
volume, cost, num_delivered, total_probing_messages, total_max_path_length, hit_ratio, table_size, micro_volume, micro_msg = flash.routing(G.copy(), payments, threshold, num_max_cache)
micro_volume_list.append(1.0*micro_volume)
micro_msg_list.append(micro_msg)
ratio_list.append(1.0*num_delivered/nflows)
hit_list.append(hit_ratio)
table_list.append(table_size)
flash_micro_volume.append(sum(micro_volume_list)/nruns)
flash_micro_msg.append(sum(micro_msg_list)/nruns)
flash_ratio.append(sum(ratio_list)/nruns)
flash_hit.append(sum(hit_list)/nruns)
flash_table.append(sum(table_list)/nruns)
with open(trace+'-'+'cache.txt', 'w') as filehandle:
for element in flash_micro_volume:
filehandle.write('%s ' % element)
filehandle.write('\n')
for element in flash_ratio:
filehandle.write('%s ' % element)
filehandle.write('\n')
for element in flash_hit:
filehandle.write('%s ' % element)
filehandle.write('\n')
for element in flash_table:
filehandle.write('%s ' % element)
for element in flash_micro_msg:
filehandle.write('%s ' % element)
def run_flash_thresh(trace, nflows, nruns, scale_factor, percentage_list,
num_max_cache):
assert (trace in VALID_TRACES)
# initialize topology and transactions from the dataset
G_ori, trans = get_topology_and_transactions(trace)
# run Flash simulation ("nruns" times) for every possible "percentage" value and record
# and average over success ratio, success volume, and number of probing messages
flash_ratio = []
flash_volume = []
flash_msg = []
for percentage in percentage_list:
G = scale_topo_cap(G_ori, scale_factor)
threshold = get_threshold(trace, trans, percentage)
print('threshold', threshold)
volume_list = []
ratio_list = []
msg_list = []
# simulate multiple runs of payments
for seed in range(nruns):
print('Start run simulation. Run', seed)
payments = generate_payments(trace, seed, nflows, trans, G)
volume, cost, num_delivered, total_probing_messages, total_max_path_length, hit_ratio, table_size, micro_volume, micro_msg = flash.routing(
G.copy(), payments, threshold, num_max_cache)
# record stats for the current run
volume_list.append(1.0 * volume)
ratio_list.append(1.0 * num_delivered / nflows)
msg_list.append(1.0 * total_probing_messages)
# average over runs and store averages
flash_volume.append(sum(volume_list) / nruns)
flash_ratio.append(sum(ratio_list) / nruns)
flash_msg.append(sum(msg_list) / nruns)
# log results to file
with open(f'{trace}-threshold.txt', 'w') as filehandle:
filehandle.write(' '.join([str(e) for e in flash_volume]) + '\n')
filehandle.write(' '.join([str(e) for e in flash_ratio]) + '\n')
filehandle.write(' '.join([str(e) for e in flash_msg]) + '\n')
def run_general(scheme, trace, nflows, nruns, nlandmarks, scale_list, percentage, num_max_cache):
G_ori = nx.DiGraph()
trans = []
if (trace == 'ripple'):
G_ori, trans = ripple_proc.setup()
if (trace == 'lightning'):
G_ori, trans = lightning_proc.setup()
threshold = get_threshold(trace, trans, percentage)
res_ratio = []
res_volume = []
res_cost = []
res_msg = []
res_hit = []
for scale_factor in scale_list:
G = nx.DiGraph()
G = scale_topo_cap(G_ori, scale_factor)
volume_list = []
ratio_list = []
cost_list = []
msg_list = []
hit_list = []
# payments to send
for seed in range(nruns):
random.seed(seed)
print 'Start run simulation. Run', seed, ' trace ', trace, ' scheme ', scheme
payments = []
if trace == 'ripple':
payments = ripple_proc.generate_payments(seed, nflows, trans, G)
if trace == 'lightning':
payments = lightning_proc.generate_payments(seed, nflows, trans, G)
if scheme == 'sp':
volume, cost, num_delivered, total_probing_messages, total_max_path_length = shortest_path.routing(G.copy(), payments)
elif scheme == 'speedymurmurs':
volume, cost, num_delivered, total_probing_messages, total_max_path_length = speedymurmurs.routing(G.copy(), payments, nlandmarks)
elif scheme == 'waterfilling':
volume, cost, num_delivered, total_probing_messages, total_max_path_length = waterfilling.routing(G.copy(), payments)
elif scheme == 'flash':
volume, cost, num_delivered, total_probing_messages, total_max_path_length, hit_ratio, table_size, micro_volume, micro_msg = flash.routing(G.copy(), payments, threshold, num_max_cache)
else:
print 'unknown routing'
volume_list.append(1.0*volume)
ratio_list.append(1.0*num_delivered/nflows)
cost_list.append(cost)
msg_list.append(1.0*total_probing_messages)
if scheme == 'flash':
hit_list.append(hit_ratio)
res_volume.append(sum(volume_list)/nruns)
res_ratio.append(sum(ratio_list)/nruns)
res_cost.append(sum(cost_list)/nruns)
res_msg.append(sum(msg_list)/nruns)
if scheme == 'flash':
res_hit.append(sum(hit_list)/nruns)
print scheme, res_cost
with open(trace+'-'+scheme+'-'+str(nflows)+'.txt', 'w') as filehandle:
for element in res_volume:
filehandle.write('%s ' % element)
filehandle.write('\n')
for element in res_ratio:
filehandle.write('%s ' % element)
filehandle.write('\n')
for element in res_msg:
filehandle.write('%s ' % element)
if scheme == 'flash':
filehandle.write('\n')
for element in res_hit:
filehandle.write('%s ' % element)