def create_topology1():
"""
1. Create a data center network object (DCNetwork)
"""
net = DCNetwork(controller=RemoteController,
monitor=True,
enable_learning=True)
"""
2. Add (logical) data centers to the topology
(each data center is one "bigswitch" in our simplified
first prototype)
"""
fog1 = net.addFogInstance("fog1")
fog2 = net.addFogInstance("fog2")
fog3 = net.addFogInstance("long_data_center_name3")
fog4 = net.addFogInstance(
"fog4",
metadata={"mydata": "we can also add arbitrary metadata to each DC"})
"""
3. You can add additional SDN switches for data center
interconnections to the network.
"""
s1 = net.addSwitch("s1")
"""
4. Add links between your data centers and additional switches
to define you topology.
These links can use Mininet's features to limit bw, add delay or jitter.
"""
net.addLink(fog1, fog2)
net.addLink("fog1", s1)
net.addLink(s1, fog3)
net.addLink(s1, "fog4")
"""
5. We want to access and control our data centers from the outside,
e.g., we want to connect an orchestrator to start/stop compute
resources aka. VNFs (represented by Docker containers in the emulated)
So we need to instantiate API endpoints (e.g. a zerorpc or REST
interface). Depending on the endpoint implementations, we can connect
one or more data centers to it, which can then be controlled through
this API, e.g., start/stop/list compute instances.
"""
# create a new instance of a endpoint implementation
rapi1 = RestApiEndpoint("127.0.0.1", 5001, net)
# connect data centers to this endpoint
rapi1.connectFog(fog1)
rapi1.connectFog(fog2)
rapi1.connectFog(fog3)
rapi1.connectFog(fog4)
# run API endpoint server (in another thread, don't block)
rapi1.start()
"""
6. Finally we are done and can start our network (the emulator).
We can also enter the Mininet CLI to interactively interact
with our compute resources (just like in default Mininet).
But we can also implement fully automated experiments that
can be executed again and again.
"""
net.start()
net.CLI()
# when the user types exit in the CLI, we stop the emulator
net.stop()
