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Control-Plane Scalability COS 597E: Software Defined Networking. Jennifer Rexford Princeton University MW 11:00am-12:20pm. Controller Scalability Challenges. Number of switches Number of control sessions Frequency of events Size of topology state Performance metrics

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jennifer rexford princeton university mw 11 00am 12 20pm
Control-Plane Scalability

COS 597E: Software Defined Networking

Jennifer Rexford

Princeton University

MW 11:00am-12:20pm

controller scalability challenges
Controller Scalability Challenges
  • Number of switches
    • Number of control sessions
    • Frequency of events
    • Size of topology state
  • Performance metrics
    • Throughput: flow rules installed per second
    • Latency: delay to handle a packet-in
nox controller
NOX Controller
  • NOX controller
    • Single-threaded, unoptimized C++ controller
    • 30K flow initiations per second
    • Sub-10ms flow install time
  • NOX-MT
    • Multi-threaded, better I/O handling, optimized malloc() implementation, …
    • On an 8-core machine, 1.6M request/sec and average response time of 2 msec
distributed controllers
Distributed Controllers
  • Better scalability
    • Smaller topology
    • Fewer events
    • Fewer flow installations
  • Better performance
    • Closer to the switches
    • Lower control-plane latency
  • Better reliability
    • Failover to a backup controller
controller configurations
Controller Configurations
  • Hierarchical
    • Global controller, with multiple local controllers
  • Peers
    • Each handling different portions of the topology, flow space, slice, or applications
  • Replicas
    • Master, with multiple slaves
    • Multiple active replicas
working with multiple controllers
Working with Multiple Controllers
  • Local scope
    • MAC learning
    • Elephant flow detection
    • Aggregate/threshold traffic statistics
  • Network-wide scope
    • Computing shortest paths
    • Selecting links to shut down to save energy
    • User mobility and virtual machine migration
discussion questions
Discussion Questions
  • Does the programmer know there is a multi-threaded/distributed controller?
    • Automated partitioning? Language constructs?
  • Does the application have to behave exactly the same as on a single controller?
    • Approximate shortest paths?
  • Do the techniques for scalability interact with the techniques for fault tolerance?
    • Shared reliable distributed data store?
  • Any useful changes to OpenFlow protocol?
going through some examples
Going Through Some Examples
  • MAC learning
  • Histogram by source IP address
  • Stateful firewall
  • Shortest-path routing
  • MAC learning at edge, shortest-path in core
  • Traffic engineering
  • Consistent updates
  • Hedera (elephant flow routing)
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