def __init__(self, *args, **kwargs):
self.switches = []
self.links = []
super(FTRouter, self).__init__(*args, **kwargs)
self.topo_net = topo.Fattree(4)
self.ip_to_id, self.id_to_ip = self.create_mappings()
self.core_switches_routing_table = {}
self.routing_table_prefixes = {}
self.routing_table_suffixes = {}
self.create_2_way_routing_table()
self.mac_to_port = {}
def __init__(self, *args, **kwargs):
super(FTRouter, self).__init__(*args, **kwargs)
self.topo_net = topo.Fattree(4)
self.k = 4
# Initialize mac address table
self.mac_to_port = {}
# Initialize arp table
self.arp_table = {}
self.sw = {}
def __init__(self, *args, **kwargs):
super(SPRouter, self).__init__(*args, **kwargs)
self.topo_raw_switches = []
self.topo_raw_links = []
self.switches = []
self.switches_links = []
self.datapath_list = []
self.mac_to_port = {}
self.fat_tree_topo = topo.Fattree(4)
self.ip_to_id, self.id_to_ip = self.create_mappings()
self.shortest_paths_for_all_nodes = self.calculate_all_shortest_path_routs_for_servers(
)
self.adjacency = collections.defaultdict(
lambda: collections.defaultdict(lambda: None))
def __init__(self, *args, **kwargs):
super(SPRouter, self).__init__(*args, **kwargs)
self.topo_net = topo.Fattree(4)
# Used for learning switch functioning
self.mac_to_port = {}
# arp table
self.arp_table = {}
self.sw = {}
self.shortest_path_dict = default_dict()
# calculate shortest paths between all server pairs
self.servers = self.topo_net.servers
self.switches = self.topo_net.switches
self.dijkstra_table, self.n_servers = dijkstra.dijkstra_shortest_path(
self.servers, self.switches)
def main(argv):
# no argument executes default case for fig 1.c
if not argv:
num_servers = 686
num_switches = 858 #245
num_ports = 14
total_pathlen_distr_Jelly = defaultdict(lambda: 0)
total_pathlen_distr_Fat = defaultdict(lambda: 0)
total_pairs = 0
# run jellyfish topology for for 10 iterations
iterations = 10
for i in range(iterations):
print(f'Iteration {i+1} / {iterations}', end='\r')
# run jellyfish topo
jellyfish_topo = topo.Jellyfish(num_servers, num_switches,
num_ports)
# jellyfish topo's servers and switches
servers = jellyfish_topo.servers
switches = jellyfish_topo.switches
# run dijkstra's algorithm on both topos
dijkstra_table = dijkstra.dijkstra_shortest_path(servers, switches)
# calculate dict['pathlength between servers']['amount of occurences'], num_pairs = total number of server pairs
length_distr, num_pairs = pathlength_distribution(dijkstra_table)
for path_len in length_distr.keys():
total_pathlen_distr_Jelly[path_len] += length_distr[path_len]
total_pairs += num_pairs
# average over all iterarions
for distance in total_pathlen_distr_Jelly.keys():
total_pathlen_distr_Jelly[distance] /= total_pairs
# run fattree topology for 1 iteration
topology = topo.Fattree(num_ports)
servers = topology.servers
switches = topology.switches
dijkstra_table = dijkstra.dijkstra_shortest_path(servers, switches)
length_distr, num_pairs = pathlength_distribution(dijkstra_table)
for path_len in length_distr.keys():
total_pathlen_distr_Fat[path_len] += length_distr[path_len]
total_pairs += num_pairs
# average results
for distance in total_pathlen_distr_Fat.keys():
total_pathlen_distr_Fat[distance] /= total_pairs
# plot figure 1.c
plot_figure_9c([total_pathlen_distr_Jelly, total_pathlen_distr_Fat],
num_servers, num_switches, num_ports, iterations)
# else if argumetns are given, execute custom
else:
network_report = False
dijkstra_report = False
run_both = False
# individually test jellyfish or fattree topology
try:
if argv[0] == 'fattree' and bool(type(int(argv[1])) == type(0)):
num_ports = int(argv[1])
iterations = 1
# optional report settings
if len(argv) == 3:
if argv[2] == '-dr':
dijkstra_report = True
elif argv[2] == '-fr':
network_report = True
dijkstra_report = True
elif argv[2] == '-nr':
network_report = True
elif argv[0] == 'jellyfish' and all(
[bool(type(int(arg)) == type(0)) for arg in argv[1:4]]):
num_servers = int(argv[1])
num_switches = int(argv[2])
num_ports = int(argv[3])
# set amount of iterations for jellyfish
if argv[0] == 'jellyfish' and argv[-2] == '-i' and bool(
type(int(argv[-1])) == type(0)):
iterations = int(argv[-1])
else:
iterations = 1
# optional report settings
if len(argv) == 5 or len(argv) == 7:
if argv[4] == '-dr':
dijkstra_report = True
elif argv[4] == '-fr':
network_report = True
dijkstra_report = True
elif argv[4] == '-nr':
network_report = True
elif all([bool(type(int(arg)) == type(0)) for arg in argv[0:3]]):
num_servers = int(argv[0])
num_switches = int(argv[1])
num_ports = int(argv[2])
iterations = 1
if len(argv) > 3:
if argv[3] == '-i' and bool(type(int(argv[4])) == type(0)):
iterations = int(argv[4])
total_pathlen_distr = defaultdict(lambda: 0)
total_pairs = 0
for i in range(iterations):
print(f'Iteration {i + 1} / {iterations}', end='\r')
# build the topo and save the servers and switches
if argv[0] == 'jellyfish':
jellyfish = topo.Jellyfish(num_servers,
num_switches,
num_ports,
network_report=network_report)
servers = jellyfish.servers
switches = jellyfish.switches
elif argv[0] == 'fattree':
fattree = topo.Fattree(num_ports,
network_report=network_report)
servers = fattree.servers
switches = fattree.switches
else:
run_both = True
jellyfish = topo.Jellyfish(num_servers,
num_switches,
num_ports,
network_report=network_report)
servers = jellyfish.servers
switches = jellyfish.switches
dijkstra_table = dijkstra.dijkstra_shortest_path(
servers, switches, report=dijkstra_report)
length_distr, num_pairs = pathlength_distribution(
dijkstra_table)
for path_len in length_distr.keys():
# print(path_len, total_pathlen_distr[path_len])
total_pathlen_distr[path_len] += length_distr[path_len]
total_pairs += num_pairs
# average results
for distance in total_pathlen_distr.keys():
total_pathlen_distr[distance] /= total_pairs
if not run_both:
num_servers = len(servers)
num_switches = len(switches)
plot_figure_9c([total_pathlen_distr], num_servers,
num_switches, num_ports, iterations)
else:
total_pathlen_distr_Jelly = total_pathlen_distr
total_pathlen_distr_Fat = defaultdict(lambda: 0)
# run fattree topology for 1 iteration
topology = topo.Fattree(num_ports)
servers = topology.servers
switches = topology.switches
dijkstra_table = dijkstra.dijkstra_shortest_path(
servers, switches)
length_distr, num_pairs = pathlength_distribution(
dijkstra_table)
for path_len in length_distr.keys():
total_pathlen_distr_Fat[path_len] += length_distr[path_len]
total_pairs += num_pairs
# average results
for distance in total_pathlen_distr_Fat.keys():
total_pathlen_distr_Fat[distance] /= total_pairs
# plot figure 1.c
plot_figure_9c(
[total_pathlen_distr_Jelly, total_pathlen_distr_Fat],
num_servers, num_switches, num_ports, iterations)
except:
raise ValueError(
'Usage: $ python topo.py (topo_type) num_servers num_switches num_ports (-report) (-iterations N'
)
def make_mininet_instance(graph_topo):
net_topo = FattreeNet(graph_topo)
net = Mininet(topo=net_topo, controller=None, autoSetMacs=True)
net.addController('c0',
controller=RemoteController,
ip="127.0.0.1",
port=6653)
return net
def run(graph_topo):
# Run the Mininet CLI with a given topology
lg.setLogLevel('info')
mininet.clean.cleanup()
net = make_mininet_instance(graph_topo)
info('*** Starting network ***\n')
net.start()
info('*** Running CLI ***\n')
script = 'performence.sh'
CLI(net, script=script)
CLI(net)
info('*** Stopping network ***\n')
net.stop()
ft_topo = topo.Fattree(4)
run(ft_topo)
# Copyright 2020 Lin Wang # This code is part of the Advanced Computer Networks (2020) course at Vrije # Universiteit Amsterdam. # Licensed under the Apache License, Version 2.0 (the "License"); you may not # use this file except in compliance with the License. You may obtain a copy # of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import topo # Same setup for Jellyfish and Fattree num_servers = 686 num_switches = 245 num_ports = 14 ft_topo = topo.Fattree(num_ports) jf_topo = topo.Jellyfish(num_servers, num_switches, num_ports) # TODO: code for reproducing Figure 1(c) in the jellyfish paper
def __init__(self, *args, **kwargs):
super(FTRouter, self).__init__(*args, **kwargs)
self.topo_net = topo.Fattree(4)
self.core_list=["10","11","12","13"]
self.pod_list=["20", "21", "22", "23", "24", "25", "26", "27", "30", "31", "32", "33", "34", "35", "36", "37"]
