Internet Research Lab at NTU, Taiwan. SIGCOMM HotSDN 2012 is the first conference workshop focused on SDN. This presentation provides a survey of selected papers in HotSDN'12 and revisits concepts and frameworks of SDN. Example applications are also presented.

1. SDN Concepts and Applications
Survey of SIGCOMM HotSDN 2012
Presenter: Jason, Tsung-Cheng, HOU
Advisor: Wanjiun Liao
Sep. 20th, 2012
1

2. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 2

3. Background
• SDN: Software-Defined Networking
– Refactoring networks by offering control platforms
– A unified system-layered abstractions
– Programmability, flexibility, and extensibility
• Network OS / Controller:
– Handling important but tedious functions
Configuring net devices, channeling states
– Presenting net abstractions, states and graphs
– Inter-network-applications control, providing API
c.f. inter-process control
3

4. Network Stack / Protocol
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http://www.conniq.com/Networking_Components7.htm

5. SDN Abstraction / Application
5
http://onrc.stanford.edu/research_unified_control_architecture.html

6. SDN Research?
• How do we scope research in SDN?
• SIGCOMM HotSDN 2012
– First Workshop in SDN
– Acceptance: 22 of 71 submissions, 31%
– 5 Stanford/Berkeley, 2 UIUC, 1 Princeton/Cornell
– 1 Nicira, 2 IBM, 2 HP, 1 Microsoft
• Mostly, implementations of newly proposed
systems, frameworks, or applications
• Very few modeling or theoretical work
• Better understanding of SDN
6

7. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 7

8. Concept of Virtualization
• Decoupling HW/SW by abstraction & layering
• Using, demanding,
but not owning or configuring
• Resource pool: flexible to slice, resize,
combine, and distribute
• A degree of automation by software
HOST 1 HOST 2 HOST 3 HOST 4,
VMs
Hypervisor:
Turns 1 server into many “virtual machines” (instances or VMs)
(VMWare ESX, Citrix XEN Server, KVM, Etc.) 8

9. Tenant View vs Provider View

10. Network Controller / OS
• DCN relies on controller for many functions:
– Address mapping / mgmt / registration / reuse
– Traffic load scheduling / balancing
– Route computation, switch entries configuration
– Logical network view ↔ physical construction
• An example: Onix
– Distributed system
– Maintain, exchange &
distribute net states
• Hard static: SQL DB
• Soft dynamic: DHT
– Asynchronous but
eventually consistent
10

11. Onix Functions
Control Plane / Applications
API
Provides
Abstraction
Logical Forwarding Plane / Network Graph
Control Logical States
Provides Commands Abstractions
Distributed Mapping Network Info Base
System Network Hypervisor Network OS
Distributes, Configures Real States
OpenFlow
11

12. Abstraction Layer
Net Control MapReduce / GFS Cluster / Tenant
Applications Master Master
Network Programming API
Language-Policy Interpreter
Network Graph
Policy-Rule Compiler Network Info Base
Configuration Manager Object DB
Verification-Debugger
Backtrace Collector
12

13. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 13

14. Hierarchical Policies
• Useful in many contexts in which resources
are shared among multiple entities.
• Express delegation of authority and the
resolution of conflicts
• Hierarchical Flow Tables (HFT): a framework
for specifying hierarchical policies in SDN
• Also proposed a compiler and runtime system
to realize policy trees
AD Ferguson et. al., “Hierarchical policies for software defined networks”, HotSDN 2012
14

15. Hierarchical Policies
A Policy Tree
Types of Hierarchy:
• Policy Priority, ex: Access Control > Routing
• IP Prefix, Longest Matching, Subnets
• Flow / Traffic Type, ex: Control PKT > Data 15

16. Hierarchical Flow Table
A rigorous definition attempting
to formalize network policies.
←Observe the symbols used by
authors here !
Matches a pkt with a policy, node internal
conflict resolution
Matches a pkt with a policy tree, using cmb recursively to
children, parent-child or inter-sibling conflict resolution
Declare policies
↓
Construct HFT
↓
Linearize & Compile HFT
Turn into flow entries on devices 16

17. Runtime HFT
Turn policy trees into
priority-indexed linear
and high-level flow
tables ↓
Turn high-level flow
tables into device
entries →
17

18. Abstraction Layer
Net Control MapReduce / GFS Cluster / Tenant
Applications Master Master
Network Programming API
Language-Policy Interpreter
Network Graph
Policy-Rule Compiler Network Info Base
Configuration Manager Object DB
Verification-Debugger
Backtrace Collector
18

19. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 19

20. Logically Centralized
• Logically centralized: multiple physical
machines hosting distributed controllers
• Net states are distributed among controllers
– What are the impact of inconsistent network view?
– How does distributed SDN states impact
performance of a logically centralized control
application?
• Depict state exchange points and trade-offs
• Provide a customized flow level simulator
D Levin et. al., “Logically centralized?: state distribution trade-offs in software
defined networks”, HotSDN 2012 20

21. State Exchange Points
State exchange points:
• App. state mgmt layer (Net. OS/Hypervisor)
• State mgmt layer network devices 21

22. Trade-Offs
• Strongly consistent
– Imposes overhead and delay, and limits
responsiveness, can lead to suboptimal
• Eventually consistent:
– Presents a temporarily inconsistent view, may
cause incorrect behavior
• Trade-off:
– performance (optimality), vs state distribution
overhead (staleness)
– Application complexity, vs robustness to
inconsistency in states
22

23. Results
• Simulation on very simple topo and workload
• Only discuss impacts on load-balancing app
• View staleness significantly impacts optimality
• Application robustness to inconsistency
increases when the application logic is aware
of distribution
• Not a very complete discussion, scenarios
are relatively simple
23

24. Abstraction Layer
Net Control MapReduce / GFS Cluster / Tenant
Applications Master Master
Network Programming API
Language-Policy Interpreter
Network Graph
Policy-Rule Compiler Network Info Base
Configuration Manager Object DB
Verification-Debugger
Backtrace Collector
24

25. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 25

26. Offloading Control ?
• Frequent and resource-exhaustive events:
– Such as flow arrivals and network state collection
– Stress the control plane and limit scalability
– As discussed in DevoFlow
• Current solutions: View as intrinsic, or try to
address by modifying switches
• How can we move control functionalities
toward datapaths, without introducing new
datapath mechanisms to switches?
S Hassas Yeganeh et. al., “Kandoo: a framework for efficient and scalable
offloading of control applications”, HotSDN 2012 26

27. Local Controllers
DevoFlow: Devolve tasks to switches
Here, perhaps switches are equipped with local controllers
Or, more local, light controllers installed near datapaths
What’s the difference?
Programmability and delay 27

28. Examples
• Does not need global network states • Shield from root controller
• Proxies of root controller • Local controllers do not propagate an
• Scale with network size event, unless root controller subscribes
• Hierarchy of controllers • Consume less bandwidth
28

29. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 29

30. Why Online Verifying?
• SDN eases development of network
applications, but bugs are still problematic
– Complexity of software will increase.
– SDN allows multiple applications or even multiple
users to program the same physical network,
potential conflicting rules
• Rule verification latency in seconds is not
enough to ensure real-time response
– Require network-wide states
– Processing churn introduce scaling challenges.
A Khurshid et. al., “VeriFlow: verifying network-wide invariants in real time”,
HotSDN 2012 30

31. VeriFlow Framework
• Prototype: Only (forwarding rule,
reachability) verification
• Equivalent classes: rules or policies
affect same type of packets or
flows, verify per class not per rule
• Rules in equivalent class are stored
as trie or prefix tree
• Generate forwarding graphs for
each class
• Processing reachability verification
by traversing forwarding graph
• Incremental, only check latest
changes, fast enough
31

32. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 32

33. Why Debugging ?
• When debugging a program:
– Pause execution at a breakpoint
– Shows the history of function calls leading to
breakpoint, a backtrace
• What bugs in SDN?
– Race condition: policy on-the-way, behind flows
– Controller logic error
– Switch implementation or policy insertion
N Handigol et. al., “Where is the debugger for my Software-Defined Network?”,
HotSDN 2012 33

34. Breakpoint and Backtrace
34

35. Architecture
35

36. Mechanisms
• Proxy: modify flow entry modification msg to
cmd switches producing postcards
• Flow Table State Recorder (FTSR): stores flow
table versions w.r.t. flow entry modifications
• Breackpoint: user-specified filtering rules
• Postcard: a truncated copy of the packet’s
header, augmented with the matching flow entry,
switch, and output port (links back to FTSR)
• Keep sending postcards to controller, all along
the way a packet traverses
• Reconstruct backtrace when a packet or a
postcard matches a filter breakpoint
36

37. Setting Breakpoint
37

38. Collecting Postcard
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39. Reconstructing Backtrace
39

40. Abstraction Layer
Net Control MapReduce / GFS Cluster / Tenant
Applications Master Master
Network Programming API
Language-Policy Interpreter
Network Graph
Policy-Rule Compiler Network Info Base
Configuration Manager Object DB
Verification-Debugger
Backtrace Collector
VeriFlow vs Debugger: Policy verification vs errant event tracing
40

41. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 41

42. Network Sensitive Applications
• Tightly integrate applications with the network
to improve performance and utilization
• To support cross-layer network control, the
SDN controller is interfaced to the master
node for each individual application, such as
the Hadoop scheduler or HBase master
• For big data applications, the SDN controller
provides an interface that accepts traffic
demand matrices from application controllers
G Wang et. al., “Programming your network at run-time for big data applications”,
HotSDN 2012 42

43. MapReduce Distributed Execution
Master also deals with:
• Worker status updates
User
• Fault-tolerance
Program
• I/O Scheduling
fork fork • Automatic distribution
fork
• Automatic parallelization
Master
assign assign
map reduce
Input Data Worker
write Output
local Worker File 0
Split 0
read write
Split 1 Worker
Split 2 Output
Worker File 1
Worker remote
read,sort
↑↑↑↑↑
Shuffle & Sort

44. Job Tracker Functions
44

45. SDN Controller Functions
45

46. Masters Work Together
How to coordinate configuration requests
among different kinds of applications?
46

47. Agenda
• Background
• Review of Onix, Net OS / Controller
• Hierarchical Policies for SDN
• State Distribution Tradeoffs
• Offloading Control Applications
• Verifying Network-wide Invariants
• Debugger and Network Backtrace
• Programming Network for Online Applications
• Programmable Enterprise WLANs
• Research Directions 47

48. Programmable WLAN
• In WiFi settings, clients choose what APs to
associate, broadcast, hard to track devices
• Interactions among APs and clients are
decentralized, hard to add functionalities
• Build a virtual AP abstraction to simplify client
management, without any client modificatoins
• Virtual AP: enables seamless mobility and
load balancing
L Suresh et. al., “Towards programmable enterprise WLANS with Odin”, HotSDN
2012 48

49. Light Virtual
Access Point
49

50. 50

51. Reference
• Teemu Koponen et al., “Onix: A distributed control platform for large-scale production
networks”, OSDI, Oct, 2010
• AD Ferguson et. al., “Hierarchical policies for software defined networks”, HotSDN 2012
• D Levin et. al., “Logically centralized?: state distribution trade-offs in software defined
networks”, HotSDN 2012
• S Hassas Yeganeh et. al., “Kandoo: a framework for efficient and scalable offloading of
control applications”, HotSDN 2012
• A Khurshid et. al., “VeriFlow: verifying network-wide invariants in real time”, HotSDN 2012
• N Handigol et. al., “Where is the debugger for my Software-Defined Network?”, HotSDN
2012
• G Wang et. al., “Programming your network at run-time for big data applications”, HotSDN
2012
• L Suresh et. al., “Towards programmable enterprise WLANS with Odin”, HotSDN 2012
51