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Runos OpenFlow Controller (eng)

About RUNOS OpenFlow controller: historical versions, current architecture, and vision

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Runos OpenFlow Controller (eng)

  1. 1. RUNOS OpenFlow controller Alexander Shalimov @alex_shali @arccnnews
  2. 2. What is SDN? Basic principles • Physical separation between forwarding plane and control plane. • Centralized management. • Programmability. • Open standards, vendor-neutral control interface Benefits • Simplify network operation (OPEX) • Reducing equipment cost (CAPEX) • New innovative services Deployments ... “SDN means thinking differently about networking” SDN = Software Defined Networking
  3. 3. SDN/OpenFlow basics A B • First packet is sent to the controller (OF_PACKET_IN). • Controller calculates the best route across the network (the lowest cost and according to the routing policies). • Appropriate OpenFlow rules are sent to switches with optional reverse route too (OF_PACKET_OUT/FLOW_MOD). A B A -> B OpenFlow controller host/client host/client switch 1 switch 2 switch 3 switch 4
  4. 4. SDN/OpenFlow basics A B • First packet is sent to the controller (OF_PACKET_IN). • Controller calculates the best route across the network (the lowest cost and according to the routing policies). • Appropriate OpenFlow rules are sent to switches with optional reverse route too (OF_PACKET_OUT/FLOW_MOD). • Dynamic reconfiguration in case of network error. A B OpenFlow controller host/client host/client switch 1 switch 2 switch 3 switch 4
  5. 5. Requirements to SDN controller • Programmability – Functionality: applications and services – Programming interface • Performance – Bandwidth – Latency • Reliability and safety – 24/7 • DC requires processing >10M events per second • Reactive controllers are more “sensitive”
  6. 6. Results of study (2013) • Maximum performance is 7 000 000 events per second. • Minimum latency is from 50 to 75us. • Shortcomings: – Reliability of controllers caused questions – Performance was insufficient [1] A. Shalimov, D. Zuikov, D. Zimarina, V. Pashkov, R. Smeliansky, "Advanced Study of SDN/OpenFlow controllers", Proceedings of the CEE-SECR '13: Central & Eastern European Software Engineering Conference in Russia, ACM SIGSOFT, October 23-25, 2013
  7. 7. RUNOS • It is a historical series of SDN/OpenFlow controllers – In-kernel – super fast, hard to develop apps – Fusion – userspace memory control interface to the kernel controller – Userspace (Easy) [main]– fully userspace controller with high functionality, easy to develop your apps, relatively high performance comparing with existing controllers – Distributed – HA version of the userspace controller • The project is in the open source (currently only userspace version) [main meaning] RUNOS = Run (fast) Operating System RUNOS = RUssian Network Operating System
  8. 8. In-kernel controller We implemented in-kernel OpenFlow controller [2]: • It is super fast – No context switching on network communication – Less time consuming memory translation procedure • It is very hard to develop your own programs – low-level programming language – limited number of libraries and tools – high risk to corrupt the whole system [2] P. Ivashchenko, A. Shalimov, R. Smeliansky "High performance in-kernel SDN/OpenFlow controller", Proceedings of the 2014 Open Networking Summit Research Track, USENIX, March 3-5, 2014 Santa Clara, USA
  9. 9. Performance (in_kernel) • Performance is 30M fps • Latency is 45us
  10. 10. Fusion: Program interface to In-kernel version 10 User space Kernel space Applications Services OpenFlow Applications Services OpenFlow Applications Services OpenFlow NOX, Pox, Floodlight, OpenDaylight, MUL, etc ARCCN +: wide range of applications -: low performance +: fast performance -: no applications What is in the middle? Offload architecture: • Apps are in userspace • Frequently used services is in kernel (e.g., topo) • Communication interface +: wide range of applications +: fast performance [3] Shalimov A., Ivashchenko P. In‐kernel offloading of an SDN/OpenFlow Controller Proceedings of the Modern Networking Technologies (MoNeTec), IEEE, Moscow, Russia, 2014
  11. 11. Experimental evaluation • The performance is 15M per second (2.5x faster). • Latency is 50us. 11 I/O throughput (cbench + l2learning), fps Response time, us
  12. 12. Programming interface Interface through shared memory: • /dev/ctrl – open kernel • ioctl() – subscribe to events • mmap() – get access to shared memory • poll() – read info from the kernel – POLLIN, POOLRDNORM, POLLRDBAND, POLLOUT • write() – flush output buffers l2 learning example code Interface is still difficult: • Low-level C • Applications require explicit synchronization among themselves • Even despite that now it is possible to use standard libraries
  13. 13. Easy RUNOS = RUNOS • Project objective – “Could an OpenFlow controller be both easy to develop applications for and also high performance?” – To develop system which will be convenient for development of new network applications – Remember about the speed and about further integration with other versions of the controller [UNDER ACTIVE DEVELOPMENT] [the main controller for now, this is what we call runos today]
  14. 14. RUNOS goals • The existing OpenFlow controllers have problems with running multiple apps independently: – Connect third party apps in one chain, hardcode for new cases, need third party apps modifications – No built-in conflict resolution system: apps might send overlapping rules (see example on the next slide) – … RUNOS is intended to solve these problems and simplify developing complex OpenFlow applications.
  15. 15. Possible problems in OpenFlow controllers Forwarding SPAN OpenFlow ip_dst: Rule 1 Rule 2 Flow table Example of the problem with running several apps independently: • Forwarding and Span apps. First app sends a flow over port 1, while second ones sends the same flow over port 5. Rules intersect with each other. • Final rules order in the flow table is unknown. • Packets will go using only the first rule. Thus, only one app will work. Conflict! • We may to resolve such conflicts and some others. Just ip_src: -> output:1,5! Rule 1: ip_src: -> output:1 Rule 2: ip_src: -> output:5 New packet never used
  16. 16. Launch options • The number of threads of the controller set – for interaction with switches – for applications • List of applications – its parameters (eg. poll-interval) – to pin the thread of execution in exclusive use (pin-to-thread, own-thread) Config (json): “controller”: { “threads”: 4 }, “loader”: { “threads”: 3 }, “link discovery”: { “poll-interval” : 10, “pin-to-thread” : 2 }, “learning switch”: { } …
  17. 17. Architecture Controller TraceTree Workers Thread pool Initialization of the controller: 1. Starting the desired number of threads 2. Starting the service components 3. Starting applications and their distribution by threads 4. Determination of the order of event processing by applications Apps Logical pipelines
  18. 18. RUNOS Details • Subscription on events – Explicitly on packet_in – Implicitly on switch up/down, port_description, stats. • Two pipelines of execution – run-to-completion • sorting the applications are running on the basis of dependences – deferred execution • TraceTree - conflict resolution and auto rules generation – Arrangement of priorities of rules, combining of rules – LOAD, MATCH, READ abstractions – MAPLE based
  19. 19. Features • Graphical user interface - enterprise network management system [4] • Wide range of applications: – L2/L3 forwarding, QoS, multipath forwarding, network virtualization, anti-DDOS, monitoring, load balancer, ACL, firewall, authentication, SPAN, NAT, ARP, DNS, DHCP, BGP, verification and troubleshooting, WiFi, OpenStack [4] A. Shalimov, D. Morkovnik, S. Nizovtsev, R. Smeliansky EasyWay: Simplifying and automating enterprise network management with SDN/OpenFlow// 10th Central and Eastern European Software Engineering Conference in Russia, CEE-SECR 2014б, ACM SIGSOFT, Moscow, Russia.
  20. 20. Performance (easy) • Performance is 10M fps (based on libfluid). • Latency is 55us. I/O throughput (cbench + l2learning), fps
  21. 21. Implementation details Keywords: C++11, QT Major third-party components: • libfluid project (_base, _msg) – for interaction with switches and parsing the OpenFlow 1.3 messages • libtins – parsing of packets in OpenFlow messages • glog (google log) – logging, multithreaded • tcmalloc (google performance tools) – alternative faster implementation of malloc/free • json11 – parsing of the configuration file • boost graph – storage of topology, calculate the route
  22. 22. Releases roadmap • Now version 0.2 – controller’s core – building topology – building a route across the network – the first version of the rules generation subsystem • Next version 0.3 – Rest API (Floodlight compatible) – WebUI • 0.4 – Applications ARP, DHCP – Optimization of performance – Statistics, metering • 0.5 – Advanced routing applications , qos – Load balancing – Firewall/ACL … • 1.0 – Management system corporate network EasyWay • 2.0 – Integration with In-kernel version (transparent for applications)
  23. 23. Distrib Runos: SDN for backbone networks Distributed OpenFlow controller ARCCN • Self-adjusting and self-organizing distributed controller for DC and WAN. – Self-adjusting as possible to ensure the specified quality of network management through scalable performance within a cluster and between clusters. – Self-organizing possible redistribution network segment between adjacent networks in case of unavailability of a dedicated cluster controllers. • Specification: – OpenFlow 1.3 – 100M flows per second – Latency is 500us – Supports up to 10000 switches
  24. 24. Distrib: Distributed OpenFlow controller Main features: • Reliability and fault tolerance (redundancy within a cluster and between clusters) • Load balancing (adding new nodes to the controller, depending on the load) • Centralized management and vision of the entire network • Working with distributed network applications • Safety and protections against external loads
  25. 25. Organization scheme • Synchronization/reservation – via DB – Special protocol – Cold, hot, warm • Additional functions – Placement of nodes of the controller in network – Redistribution of loading • migration of switches • Characteristics – Switching on the reserve controller borrows on average 50ms – Throughput decreases by 10% (for NOX with 30K to 25K) [5] Pashkov V, Shalimov A., Smeliansky R. Controller Failover for SDN Enterprise Networks // Proceedings of the Modern Networking Technologies (MoNeTec), IEEE, Moscow, Russia, 2014,
  26. 26. Conclusion • Series of OpenFlow controllers: – From fast to programmable and distributed • The project RUNOS is in the open source – OpenFlow controller • RUNOS is already used in universities and in industry (service providers, telecom operators, DCs). • We invite everyone to join the development! @alex_shali @arccnnews
  27. 27. Video about SDN • A bit of humour – SDN from different points of view –