Abstract
In SDN, the logically centralized control plane (“network OS”) is often realized via multiple SDN controllers for scalability and reliability. ONOS is such an example, where it employs Raft – a new consensus protocol developed recently – for state replication and consistency among the distributed SDN controllers. The reliance of network OS on consensus protocols to maintain consistent network state introduces an intricate inter-dependency between the network OS and the network under its control, thereby creating new kinds of fault scenarios or instabilities. In this paper, we use Raft to illustrate the problems that this inter-dependency may introduce in the design of distributed SDN controllers and discuss possible solutions to circumvent these issues.
Original language | English (US) |
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Title of host publication | APNET 2017 - Proceedings of the 2017 Asia-Pacific Workshop on Networking |
Publisher | Association for Computing Machinery |
Pages | 1-7 |
Number of pages | 7 |
ISBN (Print) | 9781450352444 |
DOIs | |
State | Published - Aug 3 2017 |
Event | 1st Asia-Pacific Workshop on Networking, APNET 2017 - Hong Kong, China Duration: Aug 3 2017 → Aug 4 2017 |
Publication series
Name | ACM International Conference Proceeding Series |
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Other
Other | 1st Asia-Pacific Workshop on Networking, APNET 2017 |
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Country/Territory | China |
City | Hong Kong |
Period | 8/3/17 → 8/4/17 |
Bibliographical note
Funding Information:SDN controllers use distributed consensus protocols, like Raft, to manage the network state and provide a highly available cluster to the underlying networking elements. Therefore, SDN controller liveness depends on all-to-all message delivery between cluster servers. In this paper, we use Raft to illustrate the problems which may be induced by this interdependency in the design of distributed SDN controllers. We also discuss possible solutions to circumvent these issues. Our preliminary results show the effectiveness of PrOG in improving the availability of leadership in Raft used by critical applications like SDN controller clusters. Acknowledgement. This research was supported in part by DTRA grant HDTRA1-14-1-0040, DoD ARO MURI Award W911NF-12-1-0385 and NSF grants CNS-1618339, CNS-1618339 and CNS-1617729.
Keywords
- Consensus
- Raft algorithm
- Resilient Routing
- SDN