1. Software-defined Networking Capabilities, Needs in GENI for VMLab (http://vmlab.oar.net) Prasad Calyam; pcalyam@oar.netpcalyam@oar.net Sudharsan Rajagopalan; srajagopalan@osc.edusrajagopalan@osc.edu Programmable Networks and GENI Session, GEC15 --October 2012--

2. Topics of Discussion VMLab SDN-GENI Projects –Capabilities, Needs for VDCloud Experiments –Capabilities, Needs for VDC-Sim Lab Exercises –Capabilities, Needs for OSU-MU Science DMZs 2

3. VDCloud Experiment in GENI 3

4. Test Scenario Paths Evaluated 4 Internet Path Route OpenFlow Path Route

5. Test Scenario Active Measurements 5

6. Rutgers – GENI Connectivity 6 http://groups.geni.net/geni/wiki/OFRGhttp://groups.geni.net/geni/wiki/OFRG - details OpenFlow and Internet path devices

7. Test Scenario Application Measurements 7 Interactive Applications consume more bandwidth and take higher task time on Internet path Video Playback consumes more bandwidth and provides higher video quality on OpenFlow path

8. Capabilities, Needs for VDCloud Experiments Path switching diversity/redundancy at edge and core –ProtoGENI nodes connected to multiple OpenFlow switches at edge, multiple programmable path selection options in core Controller framework –Proactive (pre-population of flow tables) and Reactive (flow table updates when new flow packets arrive) flow forwarding rules setup –Support handling of high-throughput traffic flows for handling large-scale VD requests and cross-traffic Controller should not crash when cross-traffic generation is high –Easier management and debugging of programmable flows Better tools to help with tedious log analysis 8

9. Capabilities, Needs for VDCloud Experiments (2) Slice I&M, management and visualization tools –Visibility for status of reserved OpenFlow resources - bandwidth consumption measurements of flows, end-to-end flow tracking –Tools for easy topology configuration, adding/deleting flows, interface configuration, sampling control of interface/flow statistics –Access to MAC address tables for debugging purposes –Ability to export network state and import back into new GENI slices 9

10. VDC-Sim 10 ‘Run Simulation’ (Offline) ‘Run Experiment’ (In GENI) Net-utility per experiment run Resource allocation of thin-clients to data centers

11. Classroom Lab Use Cases Courseware for students to get hands-on experience with computer and network virtualization concepts –Collaboration with Sonia Fahmy, Purdue University Possible VDC-Sim Exercises (“Maximize Net-Utility Score”) –Study how cloud dynamics under different fault occurrence and cross- traffic levels affects Net-utility for different number of VD request arrivals E.g., compare resource allocation schemes - Provisioning: U-RAM/F-RAM (current practice), Placement: Least Load/Least Cost/Least Latency –Explore server-side intelligent adaptation E.g., write a macro script to reduce user interaction round-trips for control actions during network health bottleneck events –Explore client-side intelligent adaptation E.g., characterize thin-clients and select thin-client encodings that delivers best QoE for different user groups – knowledge worker vs. designer/artist –Explore network-side intelligent adaptation E.g., implement new OpenFlow controller application logic to handle cyber- attacks via path switching and VD migrations; compare with current practice 11 30+ 20 - 30 0 - 20

12. Capabilities, Needs for VDC-Sim Exercises Many are similar to VDCloud experiment capabilities, needs TA sets up slice with multiple data centers and thin-clients; Student groups work with multiple OpenFlow controllers on shared resources Good documentation and examples to start from Other challenges… we will know when we try it! 12

13. OSU Science DMZ 13

14. OSU-MU Experiments Common testbed setup tasks –Federation of Ohio State U and U of Missouri - Columbia Science DMZs User accounts/roles; single sign-on; authorization policies –End-to-end (programmable) perfSONAR instrumentation & measurement –Establishment of VLAN extensions and GENI experimentation before Internet2 production deployment –Experiments with optimized large data transfers with RoCE and iWARP Research Use Case: Soybean translational genomics and breeding –MU “Soybean KB” (http://soykb.org) database experiments with OSU for set up of GENI slices to dynamically change user load patterns from remote campuses –Service response time analysis of distributed databases, web-services for remote user access’ scalability 14

15. Capabilities, Needs for OSU-MU Science DMZs Many are similar to VDCloud experiment capabilities, needs Traffic isolation between different researcher flows –Flow forwarding rules should handle policy-directed, independent traffic scheduling to remote sites Good tools, documentation, best-practices, examples – well-equip the Performance Engineer of the Science DMZ Other challenges… we will know when we try it! 15

16. Thank you for your attention! 16