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Stochastic Modeling of Packet Delay in OpenFlow SDNs Dr. Muhammad Usman Ilyas Post-doc + PhD + MS (Michigan State U), MS (LUMS), BE (NUST) [email protected], [email protected] Applied Network & Data Science Research (AN-DASH) Lab School of Electrical Engineering and Computer Science (SEECS) National University of Science and Technology (NUST) Islamabad, Pakistan 1 Team Members Uzzam Javed MS Student SEECS-NUST, Pakistan Azeem Iqbal MS Student SEECS-NUST, Pakistan 2 Center of NUST campus 3 School of Electrical Engineering & Computer Science SEECS 4 School of Electrical Engineering & Computer Science SEECS 5 nust.edu.pk 6 seecs.nust.edu.pk 7 andash.seecs.nust.edu.pk 8 Ongoing Research projects at ANDASH Lab Networking and Security 1. Packet delay model in OpenFlow SDNs (OF@TEIN) 2. OpenStack fault resilience to network errors Microsoft Research – Azure 4 research . 9 Ongoing Research projects at ANDASH Lab Networking and Security 1. Packet delay model in OpenFlow SDNs (OF@TEIN) 2. OpenStack fault resilience to network errors Microsoft Research – Azure 4 research 3. Anomaly detection in OpenStack PLUMgrid Inc., Sunnyvale, CA 4. Link de-anonymization in Ims (Tor network) Cloud-mobile Applications 1. Mobile crowdsensing to map road and traffic conditions Microsoft Research – Azure 4 research http://craters.azurewebsites.net 2. Activity recognition and tracking by smartphones HEC funding 3. MAC protocol for vehicular networks (SKKU, Suwon, S. Korea) Social media / networks 1. Word cloud segmentation based on sub-topics 10 Network Planes Data Plane Forward traffic according to the logic implemented at the control plane. 11 Network Planes Control Plane Control plane is the brain of the network, contains logic for forwarding traffic. Control plane of each switch learns structure of network by communicating with peer planes in connected switches. Control Plane Control Plane Control Plane Control Plane Control Plane 12 Network Planes Management Plane Used to manage and configure network devices. Control Plane Control Plane Control Plane Control Plane Control Plane 13 Implementation in Traditional Networks In traditional networks all three planes reside within the firmware of switches and routers. Makes the management of large networks difficult. 14 OpenFlow Software Defined Networking (SDN) is an paradigm that decouples control plane from data plane. Provides a control plane abstraction for the whole network (AS). Net Apps Net Apps Net Apps Northbound API Network Controller OpenFlow protocol Secure Channel Secure Channel Secure Channel Flow Table Pipeline Flow Table Pipeline Flow Table Pipeline Data Plane Data Plane Data Plane 16 OpenFlow Virtually separated planes interact through different APIs (interfaces). OpenFlow is an interface to communicate between the control plane and the data plane promoted by Open Networking Foundation (ONF). Net Apps Net Apps Net Apps Northbound API Network Controller OpenFlow protocol Secure Channel Secure Channel Secure Channel Flow Table Pipeline Flow Table Pipeline Flow Table Pipeline Data Plane Data Plane Data Plane 17 Separation of Control Plane across H/W Comp. Install table entry, send packet SDN Controller Most features go here This gets smaller, turns into controller to switch chip translator Control Plane CPU Packet / Network Processor 0C->p3 Table miss, send to controller dst port 0E 5 0A 1 0C 3 0A->0C 0A->0E http://colindixon.com/wp-content/uploads/2014/05/odl-meetup.pdf 18 Advantages of SDN Enables innovation by providing freedom from vendor lock-in. Improves network visibility by providing a global view. Traffic steering. Security enforcement. Makes network management simple Reduce operational cost of network. Simpler switches. 19 OpenFlow Switch Entry http://www.slideshare.net/Cameroon45/ppt-4515906 21 Research Objectives Analyzing the performance of OpenFlow SDN. Model A) packet processing delay of a single OpenFlow SDN router B) end-to-end path delay in OpenFlow SDNs. Assess the accuracy of delay modeling in mininet. 23 Prior State-of-the-art Limitation of Queuing Theory approach: Assumes Poisson arrival process for packets and exponential distribution for traffic. In reality Ethernet traffic has been found to be selfsimilar(fractal) in nature. Cannot be accurately modeled with Poisson process. Leland, Will E., et al. "On the self-similar nature of Ethernet traffic (extended version)." Networking, IEEE/ACM Transactions on 2.1 (1994): 1-15. 24 Prior State-of-the-art Some works used simulations to verify the derived model. Interaction of multiple switches were not considered. Limitation of Network Calculus approach used: A relatively new alternative to classical queueing theory. It has two branches Deterministic Network Calculus (DNC) and Stochastic Network Calculus (SNC). DNC only provides worst-case bounds on performance metrics. The models build using Network Calculus used DNC, whose result are far from practical use. Ref: Ciucu, Florin, and Jens Schmitt. "Perspectives on network calculus: no free lunch, but still good value." Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication. ACM, 2012. 25 Prior State-of-the-art Jarschel, Michael, et al. "Modeling and performance evaluation of an openflow architecture." Proceedings of the 23rd international teletraffic congress. International Teletraffic Congress, 2011. Proposed a basic model for forwarding speed and blocking probability for an OpenFlow switch and a controller using queueing theory. Azodolmolky, Siamak, et al. "An analytical model for software defined networking: A network calculus-based approach." Global Communications Conference (GLOBECOM), 2013 IEEE. IEEE, 2013 Delay and queue length boundaries are modeled using Network Calculus. 27 Prior State-of-the-art Bozakov, Zdravko, and Amr Rizk. "Taming SDN controllers in Heterogeneous hardware environments." Software Defined Networks (EWSDN), 2013 Second European Workshop on. IEEE, 2013. A simple model for control message processing using Network Calculus. Chilwan, Ameen, et al. "ON MODELING CONTROLLERSWITCH INTERACTION IN OPENFLOW BASED SDNS.” A more accurate model using queueing theory but evaluated using simulations. 28 Measurements Controlled traffic generation using traffic generator. Delay measurements will include the following components: Clock synchronization ensured using NTP 1. 2. 3. 4. Processing delay on a each switch. Queuing delay on each switch. Transmission delay on each switch. Link propagation delay. 29 Evaluation Parameters Following possible measurement scenarios will be considered: Based on traffic: Packet size Traffic distribution Rate TCP/UDP Variable switching load OpenFlow Parameters: Single field matching Multiple field matching Matching on a range of IP's/Port numbers Changing the number of actions Hard time out/ Soft time out Comparison between reactive and proactive forwarding. 30 Platform 1 - Mininet C0 Controller SDN emulator To study the delay in OpenFlow SDN switches in an SDN emulator. OpenFlow Switch H1 S1 H2 Virtual Hosts Mininet Virtual Machine 31 Platform 2 – Laboratory setup Experimentation on lab scale testbed of OpenFlow SDN switches. Enabling OpenFlow on a Mikrotik RouterBoard 750GL router, for experimentation. Controller OpenFlow switches Mikrotik RouterBoard 750GL switches Host 1 Host 2 32 Platform 3 – GENI Testbed An Internet scale network testbed infrastructure, spanning across the US. Experimentation on widely distributed resources. To explore behavior of OpenFlow switches at scale. http://groups.geni.net/geni/wiki/GeniNewcomersWelcome 33 Platform 4- OF@TEIN Risdianto, Aris Cahyadi, and JongWon Kim. "Prototyping Media Distribution Experiments over OF@ TEIN SDN-enabled Testbed." Proceedings of the Asia-Pacific Advanced Network 38 (2014) 34 Platform 4- OF@TEIN OF@TEIN is a an OpenFlow enabled testbed spread over seven countries. Project was launched in July 2012, through Korean Government funding. Deployed on TEIN4 (Trans-Eurasia Information Network 4). Managed by Consortium of Korean universities International collaboration sites Led by Gwangju Institute of Science & Technology (GIST), S. Korea. 35 Some Initial Results for Single Switch Three platforms were used to analyze the round trip time delay. OF@TEIN results pending due to ongoing migration to OpenStack. Using Distributed Internet Traffic Generator (D-ITG) for all platforms. 1,000,000 packets were generated with a constant rate of 10,000 pkt/s from one host to another. Size of packet was kept constant to 1,500 bytes. TCP protocol was used. All platforms were using Open vSwitch (OVS) and OpenFlow 1.0 enabled switches. Each platform was tested for reactive and proactive forwarding scenario. 36 Single Router Delay 37 Mininet Traffic was generated on a single switch with external controller (POX). Timeout for switch’s flow table entry was set to 1 second. OpenFlow switch was invoked as L2 learning switch through controller. 38 Mininet 39 Mininet Traffic was generated on a single switch. Entries on the switch were pre-loaded before the flows were generated. 40 Mininet 41 Laboratory Setup Traffic was generated on a single switch, MikroTik RouterBoard 750GL. Controller (POX) was running in one system, which invoked OpenFlow switch to act as a L2 learning switch. Timeout for flow table entry was set to 1 second. 42 Laboratory Setup 43 Laboratory Setup Traffic was generated on a single switch, MikroTik RouterBoard 750GL. The entries on the switch were proactively added before the flows were generated. 44 Laboratory Setup 45 GENI Testbed Traffic was generated on a single switch on GENI testbed. Controller (POX) was running in Utah, while switch and hosts were located in California. Timeout for switch’s flow table entry was set to 1 second. OpenFlow switch was invoked to act as L2 learning switch. 46 GENI Testbed 47 GENI Testbed Traffic was generated on a single switch on GENI testbed. The switch and hosts were all located in California. The entries on the switch were proactively added before the flows were generated. 48 GENI Testbed 49 End-to-end Delays 50 Some Initial Results for End-to-End measurements Three platforms were used to analyze the round trip time delay. 1,000,000 packets were generated with a constant rate of 10,000 pkt/s from one host to another. Size of packet was kept constant to 1,500 bytes. TCP protocol was used. All platforms were using Open vSwitch (OVS) enabled switches. 51 Mininet Traffic was generated on two switches with external controller(POX). Timeout for switch’s flow table entry was set to 1 second. OpenFlow switch was invoked as L2 learning switch through controller. 52 Mininet 53 Mininet Traffic was generated on two switches. The entries on the switch were proactively added before the flows were generated. 54 Mininet 55 Laboratory Setup Traffic was generated through two MikroTik RouterBoard 750GL switches. Controller (POX) was running in one system, which invoked OpenFlow switches to act as a L2 learning switch. Timeout for switch’s flow table entry was set to 1 second. 56 Laboratory Setup 57 Laboratory Setup Traffic was generated through two MikroTik RouterBoard 750GL switches. The entries on the switch were proactively added before the flows were generated. 58 Laboratory Setup 59 Thank You 60