1. The document discusses SDN interfaces, performance analysis of SDN components, and network functions virtualization. 2. It analyzes the performance of SDN controllers and the data plane, and provides models to evaluate the performance of the SDN architecture under different conditions. 3. The document also examines network functions virtualization, including placement of virtualized network functions and performance evaluation of a virtualized firewall.

1. Institute of Computer Science
Department of Distributed Systems
Prof. Dr.-Ing. P. Tran-Gia
SDN Interfaces and
Performance Analysis of SDN components
Steffen Gebert, David Hock, Michael Jarschel, Thomas Zinner,
Phuoc Tran-Gia
www3.informatik.uni-wuerzburg.de

2. Agenda
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Steffen Gebert
u „A Compass for SDN“
§ Interfaces
§ Features
§ Use cases
u Performance of the SDN architecture
§ Data Plane Performance
§ Control Plane Performance
§ Analytical Model
u Network Functions Virtualization
§ Placement in a Mobile Network
§ Performance Evaluation a virtualized network function

3. IEEE Communications Magazine, June 2014
M. Jarschel, T. Zinner, T. Hossfeld, P. Tran-Gia, W. Kellerer
A COMPASS FOR SDN
SDN Interfaces and Performance Analysis of SDN Components 3
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4. Interfaces…
Applica8on
Control
Plane
Northbound
API
SDN
Network
Control
Plane
Switch
Switch
SDN
WAN
SDN
Network
Control
Plane
SDN Interfaces and Performance Analysis of SDN Components 4
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Switch
Network
Control
Module
Southbound
API
Network
Control
Module
Applica8on
Control
Interface
Applica8on
Control
Module
Applica8on
Control
Module
Applica8on
Control
Module
Westbound
API
Hypervisor
vSwitc
h
Hypervisor
vSwitc
h
Hypervisor
vSwitch
Cloud
Eastbound
API
User
Legacy
Network
Control
Plane
Legacy
WAN
User
User

5. ….Features…
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u Programmability
§ Principle and also key feature of SDN
§ Opens control plane to innovation and enables customization
u Protocol independence
§ Compatibility with other networking technologies & protocols
§ Enables technology migration and application-tailored network stacks
u Ability to dynamically modify network parameters
§ Active modification of network parameters close to real time
§ Enables fast and flexible adaptation in changing environments
u Granularity
§ Control of traffic flows on varying aggregate level and protocol layers
§ Ensures scalability of the control plane to work on different levels
u Elasticity
§ Describes the ability of the SDN control plane to scale up and down
§ Enables the control plane to react to variations in traffic mix and volume.

6. …and Use Cases
u Cloud Orchestration: Provisioning and operation of cloud applications
requires integrated management of network and cloud framework
u Load Balancing: Integration of load balancing within network forwarding
elements operating on different granularities
u Routing: Centralized control plane in SDN provides ample opportunities for
SDN Interfaces and Performance Analysis of SDN Components 6
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routing protocol adaptation
u Monitoring and Measurement: Ability to perform certain network
monitoring operations and measurements without additional overhead
u Network Management: Automatic adaptation of network policies based on
monitoring information
u Application-Awareness: Better cross-layer optimization between
applications and network capabilities

7. Use-Cases and Interfaces
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Interface
Use Case
Southbound
Interface
Northbound
Interface
Eastbound
Interface
Westbound
Interface
Cloud
Orchestration
✔
✔
X
X
Load Balancing
✔
✔
X
✔
Routing
✔
X
✔
✔
Monitoring and
Measurement
✔
✔
✔
✔
Network
Management
X
✔
✔
X
Application-
Awareness
X
✔
X
X

8. EXAMPLE: CLOUD
ORCHESTRATION
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9. Migration – Intra DC
SDN
Network
Control
Plane
VM1
VM2
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Energy
Op?mizer
QoE
Op?mizer
Switch
VM3
Switch
Switch
Cloud
Mgmt.
Module

10. Migration – Intra DC
Cloud
Mgmt.
Module
Switch
VM1
VM2
Energy
Op?mizer
QoE
Op?mizer
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VM3
Switch
Switch
SDN
Network
Control
Plane

11. Migration – Intra DC
Cloud
Mgmt.
Module
Switch
VM1
VM2
Energy
Op?mizer
QoE
Op?mizer
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VM3
Switch
Switch
SDN
Network
Control
Plane

12. Migration – Inter DC
Energy
Op?mizer
QoE
Op?mizer
QoE
Op?mizer
Network
Control
WAN
Op?mizer
Network
Mgmt.
Module
Switch
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SDN
Network
Control
Plane
VM1
VM2
VM3
Cloud
Mgmt.
Module
Switch
Switch
Energy
Op?mizer
Cloud
Mgmt.
Module
SDN
Network
Control
Plane
Switch
Switch
SDN
Network
Control
Plane
Switch
Switch
Switch

13. Migration – Inter DC
Energy
Op?mizer
QoE
Op?mizer
QoE
Op?mizer
Network
Control
WAN
Op?mizer
Network
Mgmt.
Module
Switch
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SDN
Network
Control
Plane
VM2
VM3
Cloud
Mgmt.
Module
Switch
Switch
Energy
Op?mizer
Cloud
Mgmt.
Module
SDN
Network
Control
Plane
Switch
Switch
SDN
Network
Control
Plane
Switch
Switch
Switch
VM1

14. Migration – Inter DC
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u Problems:
§ Variability of traffic
§ Application requirements
§ Interaction between controllers
§ etc…
B4: Software-
Defined WAN
(Google, ACM
Sigcomm 2013)

15. Current Research Topics
u Performance evaluation of the SDN architecture
u (Controller placement and controller architectures)
u (SDN-based application and network interaction)
u NFV – placement and performance
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16. PERFORMANCE OF THE SDN
ARCHITECTURE
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17. Performance of the SDN Architecture
u Performance of the data plane
u Performance analysis of SDN Controller
u Modeling and performance evaluation of the SDN architecture
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18. Performance of the Data Plane
u Analysis of throughput and processing delays of OpenFlow enabled
forwarding devices
§ Open vSwitch
§ NetFPGA
§ Pronto OpenFlow-enabled switch
u Testbed to measure data plane
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performance of devices
§ Link rate of 1Gbit/s
§ Endace DAG card to
capture traffic

19. Results – Number of Forwarding Rules
u Processing delay for a nearly empty (one rule) and a full flow table
u Significant impact of payload length on processing delays
u High impact of flow table entries on NetFPGA performance
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20. Results – Forwarding to Controller
u Impact on processing delays by forwarding all packets to NOX controller
u Massive packet loss between 95% and 99%
u Significantly increased processing times
u Controller acts as bottleneck in this scenario
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21. Performance Analysis of SDN Controllers
u Analysis of KPIs of SDN controller software in realistic environments
§ Throughput, latency, CPU & RAM, IAT,…
§ Holistic framework for different OpenFlow versions
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u Implementation of OFCProbe
§ Emulates data plane message and resulting
control plane traffic
u Features
§ Generated control messages per switch
§ Topology emulation and PCAP file playback
§ Incoming data packets can be arbitrarily distributed

22. Outstanding Packets: Floodlight
u Floodlight: Uniform handling of particular switches - consistent behavior
u Nox: Non-uniform handling – “waves” detectable
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23. Performance Evaluation of SDN
u Investigation of the performance of the SDN architecture for changing
parameters
§ Modeling of control and data plane
§ System scalability and limitations of the concept
u Evaluations using analytical modeling and simulations
§ Input parameters based on measurements with real hardware
§ Verification of analytical results with simulations
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u Simulation of OpenFlow
§ OpenFlow implementation for OMNeT++: OFOmnet
§ Code available at https://github.com/lsinfo3/ofomnet

24. Simple Model of SDN
u Abstraction as feedback-oriented queuing system model
§ Forward queueing system of type M/GI/1
§ Feedback queueing system M/GI/1-S
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25. Results for Different Forwarding Probabilities
u Impact of different forwarding probabilities on the average packet
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sojourn time
u Mean sojourn time increases for increasing controller load and for
increasing forwarding probability

26. SDN Performance: Summary
u Performance analysis of SDN architecture and SDN control plane
§ Controller analysis using OFCProbe
§ Performance evaluation of the architecture using models
u Main results of the current investigations
§ Diverse behavior of software control planes, e.g., Floodlight
outperforms NOX in terms of throughput and fairness
§ Scalability mainly depends on control plane
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u Other issues:
§ Investigation of different topologies and software controllers
§ Integration and investigation of OpenFlow 1.3
§ Impact of messages via Northbound interface
§ Extension of the analytical models

27. NFV – PLACEMENT AND
PERFORMANCE
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28. Network Functions Virtualization
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29. NFV in Mobile Networks
u Problem: Mobile Core consists of numerous expensive, proprietary,
overdimensioned middle boxes.
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u Idea:
§ Move network function into software (NFV)
§ Run and orchestrate it in cloud
u Advantages:
§ Shorter release cycles
§ Elasticity
§ Flexibility
u Showcase: Dynamic instantiation of Serving Gateways (SGW) in case of
increased resource usage caused by “mega events”
Photo: Ericsson

30. SDN Legacy SDN
Legacy SDN
Cloud Infrastructure
with virtualized
appliances and
virtualized network
functions
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SDN
Controller
Network
Management
Security Rules
External
network
A1
A2
VNF 1
IT client IT client
Use case : Network Function
Cloud
Controller
Smartphone
Cloud NFV & SDN

31. NFV: Placement and Performance of VNFs
u Performance analysis of virtualized network functions
u Placement of virtualized network functions (VNFs)
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32. SDNA – Software Defined NFV Application
MEGA EVENT USE CASE
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33. Mobile Network Infrastructure
Home Ben Event
NUC* CAM*
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NE+
Operator
Control Center
Ann
* CAM Cloud Application Manager
NUC Network Utilization Control
POCO Pareto-Optimal Resilient Controller
SGW Serving Gateway
POCO*
SGW
Data center
SGW
Controller
SGW
App

34. Increased Resource Requirements for Mega Events
Ann
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Event Area
Ann
Ben
Home Area
Ben
Home Area
Event Area

35. Planning Infrastructure on Demand
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36. Flexible Reuse of Existing Infrastructure
1. Deploy SGW App and Controller à CAM
2. Program virtual GW à SDN+CAM
NUC* CAM*
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3. Security check
Home Ben Event
SGW
Operator
Control Center
* CAM Cloud Application Manager
NUC Network Utilization Control
POCO Pareto-Optimal Resilient Controller
SGW Serving Gateway
POCO*
SGW
SGW
Controller
SGW
App
Ann
Video
call
Data center
SGW
Controller
SGW
App
Video
call

37. Virtualized Network Functions in Operator Cloud
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Ø Scalability
Ø Redundancy
Ø Flexibility
Ø Open Source platform
CAM
NUC

38. PERFORMANCE OF
VIRTUALIZED NETWORK
FUNCTIONS
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39. Performance of Virtualized Network Functions
u Impact of softwarization on performance of network functions
§ Impact on typical KPIs, i.e., delay, throughput
§ Influence of dynamic function placement
u Categorization and Modeling of VNFs
§ By resource demands: CPU-intense, network-intense, etc.
§ By ability to scale out: scale out delay, state-sync, etc.
§ Identification and investigation of characteristic VNFs
§ Analysis of the influence of the virtualization platform
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40. Performance of a Virtualized Firewall
u Comparison of Cisco ASA/ASAv in a dedicated testbed
§ Cooperation with the computing center of UniWü
u Measurement-based comparison of virtualized and hardware
Cisco ASA Firewall
§ Data plane performance (throughput, connection setup)
§ Configuration and monitoring via REST API
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u Entities under investigation:
§ ASA Service Module (Hardware)
§ ASAv on vmware / KVM
External
network
Internal
network
Firewall
Module

41. Summary
u SDN interfaces are key to integration and better user experience
§ Interaction with legacy infrastructure and cloud controller
§ Tailored handling of traffic flows or aggregates
§ Application-aware networking ensures optimal user experience
u SDN control plane is performance-critical for the whole network
§ Measurement and simulation tools provided
§ Suggestion of (simple) analytical model
§ Optimal controller placement and hierarchy under investigation
u Network Functions Virtualisation (NFV) as logical step, supported by SDN
§ Open issues regarding performance of pure software implementations,
interfaces, placement, operations, monitoring, ...
§ Benefit: Flexibility of the network as we know it from software
§ Mobile network operators are planning rollout of virtualized EPC
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