The Role of Inter-Controller Traffic in SDN Controllers Placement
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The document discusses the impact of inter-controller traffic on the placement of software-defined networking (SDN) controllers, highlighting the importance of consistency models for data synchronization among controllers. It emphasizes the trade-offs between single and multiple data ownership models and presents formulas for estimating reactivity perceived by switches due to interactions. The findings indicate that the choice of data owner and latency among controllers are critical for optimizing controller placement and enhancing network performance.
![Optimal controller placements
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70
050100150200250300350400
Reaction time for MDO [ms]
ReactiontimeforSDO[ms]
OptimalSDOplacement
OptimalMDOplacement
3 controllers in large ISP
For Single Data-Ownership (SDO), 3 possible data owners](https://image.slidesharecdn.com/sdn-giaccone-161116131031/85/The-Role-of-Inter-Controller-Traffic-in-SDN-Controllers-Placement-12-320.jpg)
![Conclusions
• single/multiple data-ownership models adopted
by real SDN controllers affect strongly the
performance perceived at the network devices
• reactivity formulas allow to devise the optimal
placement of the controllers
– the latencies among controllers are crucial in SDO
model
• in the SDO model the choice of the data owner is
crucial
• accurate validation of the given formulas in a
large SD-WAN controlled by OpenDaylight
– available on extended version [1] on arxiv
15](https://image.slidesharecdn.com/sdn-giaccone-161116131031/85/The-Role-of-Inter-Controller-Traffic-in-SDN-Controllers-Placement-14-320.jpg)
The Role of Inter-Controller Traffic in SDN Controllers Placement
- 1. The Role of Inter-Controller Traffic in SDN Controllers Placement Tianzhu Zhang, Andrea Bianco, Paolo Giaccone IEEE NFV-SDN: Palo Alto, CA November 8th, 2016 1
- 2. Software Defined Networking • programmability • enabled by centralized view of the network state Advantages • scalability for large networks One relevant challenge 2
- 3. Distributed controllers • fault-tolerance and resilience • load balancing, thus higher scalability Motivation • how the network state is distributed across the controllers to allow a centralized logical view Critical issue 3
- 4. Control-plane in distributed controllers • in-band for large networks (e.g. SD-WAN) • switch-controller (Sw-Ctr) traffic – standard protocols (e.g. OpenFlow) • controller-controller (Ctr-Ctr) traffic 4 Switch-controller traffic Inter-controller traffic
- 5. Inter-controller (Crt-Ctr) traffic • needed to synchronize the controllers’ states – shared data structures • generated by consistency protocols – ad-hoc protocols – different models for consistency 5
- 6. Consistency models • assume a shared table=(key,value) • strong consistency – any read(key) returns always the same value • eventual consistency – any read(key) returns eventually the same value • adopted model affects heavily – the mechanisms to distribute and update the data – the reactivity of the SDN controllers perceived by the network devices – the correct behavior of the network • e.g. inconsistent view of the network graph may lead to routing loops 6
- 7. Consistency in SDN controllers • eventual consistency • anti-entropy algorithm • network topology • flow rules • flow statistics • strong consistency • RAFT consensus algorithm • switch-controller mapping • distributed locks ONOS • strong consistency • RAFT consensus algorithm • all shared data structures OpenDaylight 7
- 8. Data-ownership model • Consistency model affects that controller owner of the shared data 8 • Read/write operations always forwarded by the local controller to the data-owner controller • distributed architecture only for high availability • e.g. strong consistent data structures Single data-ownership (SDO) model • Read/write operations are local and then forwarded (asynchronously) to the other controllers • e.g. eventual consistent data structures Multiple data-ownership (MDO) model
- 9. Our main contributions • we provide formulas to estimate the reactivity perceived at the switch due to the Sw-Ctr and Ctr-Ctr interactions • we show the performance tradeoffs for the controller placement problem 9
- 10. Reactivity for Multi Data-Ownership Switch S1 ResponseUpdate data Flood update Data owner controller TR TR = Sw-Ctr RTT Data owner controller Data owner controller
- 11. Reactivity for Single Data-Ownership Data owner controller Switch S1 Raft request Log replicatiom ResponseUpdate data Log reply Log commit Controller Controller Hp: RAFT algorithm for strong consistency TR TR = Sw-Ctr RTT+2 Ctr-Ctr RTT
- 12. Optimal controller placements 13 0 10 20 30 40 50 60 70 050100150200250300350400 Reaction time for MDO [ms] ReactiontimeforSDO[ms] OptimalSDOplacement OptimalMDOplacement 3 controllers in large ISP For Single Data-Ownership (SDO), 3 possible data owners
- 13. The role of data owner in SDO Choosing carefully the data owner is very important for the reactivity 14 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 0100200300400500600700800900 Reduction factor Placementid Maximum Minimum Minimum reduction factor = Reactivity (2nd best data owner choice) Reactivity (best data owner choice) Maximum reduction factor = Reactivity (worst data owner choice) Reactivity (best data owner choice)
- 14. Conclusions • single/multiple data-ownership models adopted by real SDN controllers affect strongly the performance perceived at the network devices • reactivity formulas allow to devise the optimal placement of the controllers – the latencies among controllers are crucial in SDO model • in the SDO model the choice of the data owner is crucial • accurate validation of the given formulas in a large SD-WAN controlled by OpenDaylight – available on extended version [1] on arxiv 15