Traffic Optimization inMulti-Layered WANs using SDN Presented by Henrique Rodrigues (1,2), Inder Monga (2), Abhinava Sadasivarao (3), Sharfuddin Syed (3), Chin Guok (2), Eric Pouyoul (2), Chris Liou (3), Tajana Rosing (1) at IEEE Symposium on High Performance Interconnects, August 2014 1:UCSD, 2: ESNet/LBNL, 3: Infinera

1. Traffic Optimization in Multi-Layered WANs using SDN
Henrique Rodrigues1,2, Inder Monga2, Abhinava Sadasivarao3, Sharfuddin Syed3, Chin Guok2, Eric Pouyoul2, Chris Liou3, Tajana Rosing1
1UCSD, 2ESNet/LBNL, 3Infinera
IEEE Symposium on High Performance Interconnects, August 2014

2. Wide Area Networks
• Critical resource for performance and
reliability of the Internet
• Massive traffic from multiple applications
over several long distance links
• Equipment from multiple vendors
– Expensive to deploy, expensive to operate
• Problems:
– Poor resource utilization (~30-50%)
– Low management flexibility
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New%York%
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Dublin%
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Tuesday, August 13, 13
Figure source:
Microsoft SWAN
SIGCOMM’2013
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3. Recent work addressing these
problems in inter DC WAN:
•Google’s B4 (SIGCOMM’13)
•Microsoft SWAN (SIGCOMM’13)
Improved network utilization, flexibility, resilience with Centralized management + Software Defined Networking + OpenFlow
Inter DC Wide Area Networks
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4. OpenFlow, BGP
(B4, SWAN)
GMPLS, TL1
Proprietary
Manual Operation
The hidden multi-layered infrastructure
TDM/Transport
SONET, SDH
DWDM/OADM
IP
OpenFlow Layer
Can we manage all layers using a unified abstraction?
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5. Why is this important?
•Scenarios where dynamic management wins:
–Multi-layer traffic optimization
•Current WAN management assume static topology
•If demand grows, new paths are added manually
•In the limit, current solutions either throttle traffic (SWAN, B4) or offer degraded service
–Bandwidth virtualization
•Static allocation of higher capacity optical pipes can result in wasted capacity for variable demands
–Flows of different demand (mice vs. elephant)
•Interaction of flows might lead to lower utilization
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6. Optical Transport Network
0
250
500
750
1000
0 10 20 30
Throughput (Mbps)
0
250
500
750
1000
0 10 20 30
Concurrent flows C = 4 Concurrent flows C = 8
Time (s) Time (s)
Packet Network
Site A Site B
Distinct TCP Flows vs. Utilization
10G Optical Circuit
C concurrent
small, short
flows
Large flow
Congestion control
triggered by intermittent
small flows contributes
to poor utilization
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7. Summary of Challenges for Unified WAN Network Management
–Network representation:
•How to build a complete view of the network?
–Multiple management interfaces:
•OpenFlow, SNMP, GMPLS, TL1
–Equipment with different characteristics:
•Encapsulation, Forwarding, Queuing, Link Sharing
–Distinct Traffic visibility
•Packet Flows, TDM slots, Wavelengths
–Management granularity
•Single L3 flow vs. Wavelength with several flows
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8. Multi-layer orchestration with OSCARS-TE
REST/JSON
OpenFlow 1.0
Configuration Manager
Topology Exchange
Multi-Layer
Path Engine
Multi-Layer
Provisioning
Multi-Layer Topology App
ESNet Circuits Reservation System (OSCARS)
SDN Controller
Floodlight
Traffic Optimization Engine
OSCARSTE Multi-Layer SDN Management Modules
Optical Transport
Network
Packet Network
X
Y
Z
A, B, C – Packet Switches X, Y, Z – Optical Transport
A
B
C
Site A
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9. Orchestrating a Multi-layer SDN: Discovering and maintaining topology
•No inter-layer discovery protocols
•Maintenance of topology likely manual in the near term
•Dynamic Topology construction for multi-layer
•LLDP discovers L2 topology when L0/1 is in place
•Configuration manager communicates proprietary L0/L1 topology. Alternatively, L0/L1 topology can be scanned
•OSCARSTE constructs a multi-layer topology annotating link with capacities, granularity and flow capabilities
Configuration Manager
Topology Exchange
Multi-Layer
Path Engine
Multi-Layer
Provisioning
Multi-Layer Topology App
ESNet Circuits Reservation System (OSCARS)
SDN Controller
Floodlight
Traffic Optimization Engine
OSCARSTE
Multi-Layer SDN
Management Modules
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10. Orchestrating a Multi-layer SDN: Opening New Paths
•Path Computation Engine multi-layer aware
•Multi-stage, multi-layer computation process
–Prunable constraints (ex. Bandwidth), Additive constraints (ex. Latency), non-additive constraints (ex. VLAN continuity), Cross-Layer adaptation constraints.
•In this work we flatten the topology into a single graph annotated with node/link capabilities
Configuration Manager
Topology Exchange
Multi-Layer
Path Engine
Multi-Layer
Provisioning
Multi-Layer Topology App
ESNet Circuits Reservation System (OSCARS)
SDN Controller
Floodlight
Traffic Optimization Engine
OSCARSTE Multi-Layer SDN Management Modules
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11. Orchestrating a Multi-layer SDN:
Provisioning at multiple layers
• Match capabilities of the layers with the
provisioning action
• Capabilities learnt from OF handshake
• Smart path setup with low impact on traffic
• Ordered path updates between L2 and L1 devices
• Pluggable with public SDN controller APIs
Configuration
Manager
Topology
Exchange Multi-Layer
Path Engine
Multi-Layer
Provisioning
Multi-Layer
Topology App
ESNet Circuits Reservation System (OSCARS)
SDN Controller
Floodlight
Traffic
Optimization
Engine
OSCARSTE
Multi-Layer SDN
Management Modules
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0"
2.5"
5"
0" 5" 10" 15" 20"
Throughput"(Gbps)"
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12. Orchestrating a Multi-layer SDN: Dynamic provisioning based on demand
•This is our multi-layer optimization engine
•Offloading engine allocates new paths when demand grows and isolate traffic with different characteristics
•Port-based monitoring with threshold-driven triggers
•Sub-flow insight using packet sampling
•Mapping flows to topology and new links requires multi-layer knowledge
Configuration Manager
Topology Exchange
Multi-Layer
Path Engine
Multi-Layer
Provisioning
Multi-Layer Topology App
ESNet Circuits Reservation System (OSCARS)
SDN Controller
Floodlight
Traffic Optimization Engine
OSCARSTE Multi-Layer SDN Management Modules
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13. Optical Transport Network
Packet Network
Site A Site B
Enabling predictable application performance
Small flows
Large flow
T = 0: Only small flows
T = 30: Large data transfer started
T = 55: Large data transfer offloaded
to dynamically allocated circuit
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14. Conclusion
•Multi-layer traffic optimization improves network performance and utilization
•Planned topology minimize performance degradation during offloading
•Intelligent multi-layered SDN control plane enables practical bandwidth virtualization and predictable application performance
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15. Thank you!
Henrique Rodrigues, Tajana Rosing
{hsr,tajana}@eng.ucsd.edu
Inder Monga2, Chin Guok2, Eric Pouyoul2,
{inder,chin,lomax}@es.net
Chris Liou3, Abhinava Sadasivarao3, Sharfuddin Syed3,
{cliou,asadasivarao,ssyed}@infinera.com
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This work was supported by Energy Sciences Network, which is funded by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR). ESnet is operated by Lawrence Berkeley National Laboratory, which is operated by the University of California for the U.S. Department of Energy under contract DE-AC02-05CH11231.