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QoE-Aware Traffic Steering using OpenFlow

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QoE-Aware Traffic Steering using OpenFlow presentation by Prasad Calyam, U. Missouri at US Ignite ONF GENI Workshop on October 8, 2013

QoE-Aware Traffic Steering using OpenFlow presentation by Prasad Calyam, U. Missouri at US Ignite ONF GENI Workshop on October 8, 2013

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  • 1. QoE-Aware Traffic Steering using OpenFlow Prasad Calyam, Ph.D. US Ignite and ONF Workshop, October 8th 2013 Research Sponsors: NSF (CNS-1050225, CNS-1205658), VMware, Dell, IBM http://vmlab.oar.net
  • 2. Discussion Topics • User QoE Problem Context • Solution Approach and Results • “One more thing…” 2
  • 3. Discussion Topics • User QoE Problem Context • Solution Approach and Results • “One more thing…” 3
  • 4. Virtual Desktop Clouds (DaaS) “Brain of the Cloud” P. Calyam, R. Patali, A. Berryman, A. Lai, R. Ramnath, “Utility-directed Resource Allocation in Virtual Desktop Clouds”, Elsevier Computer Networks Journal (COMNET), 2011. 4
  • 5. Example DaaS Use Cases (a) Virtual classroom lab involving faculty and students (b) Computationally intensive interactive applications for biomedical community (e.g., remote volume visualization) (c) Simulation-as-a-Service requiring HPC resources for advanced manufacturing (d) Virtual desktops for underserved communities 5 P. Calyam, A. Berryman, A Lai, M. Honigford, “VMLab: Infrastructure to Support Desktop Virtualization Experiments for Research and Education”, VMware Technical Journal (Invited Paper), 2012.
  • 6. Research Scientist Home User Mobile User Fixed Resource Allocation Model • High consistent CPU • High consistent memory • High bandwidth connectivity • Low bursty CPU • Low bursty memory • Medium bandwidth connectivity • Low bursty CPU • Low bursty memory • Low bandwidth connectivity CPU Memory Bandwidth VDCs Today – Overprovisioning and Guesswork… Available Resources Number of Users VDC Service Provider Unified Resource Broker = 6
  • 7. Overprovisioning and Guesswork Fails! Home User Mobile User VDC Service Provider • Inadequate CPU, memory and bandwidth (Impact e.g., Slow interaction response times) • Calls from unhappy customers • High operation $$ Problem: Resource allocation without awareness of system, network and user experience characteristics • Inadequate CPU, memory and bandwidth (Impact e.g., IPTV with impairments and slow playback) • Excess CPU, memory and bandwidth (Impact e.g., Good interaction response times and smooth IPTV playback) Research Scientist 7
  • 8. VDCs in the Future – Smart thin-clients at user sites Smart Thin-Client Smart Thin-Client VDC Service Provider • Happy customers • Low operation $$ Research Scientist Home User Mobile User CPU Memory Bandwidth • Utility-directed CPU, memory and bandwidth (Impact e.g., Good interaction response times and smooth IPTV playback) Unified Resource Broker Utility-directed Dynamic Resource Allocation Model (U-RAM) = 8 NOTE: Application behavior profiles collected from smart thin-client feedback also help in QoE degradation troubleshooting!** ** Y. Xu, P. Calyam, D. Welling, S. Mohan, A. Berryman, R. Ramnath, “Human-centric Composite Quality Modeling and Assessment for Virtual Desktop Clouds”, ZTE Communications Journal (Invited Paper), 2013.
  • 9. VD Placement after U-RAM Provisioning • URB Placement decisions involving data centers are influenced by: – Session latency, Load balancing, Operation cost • Placement decisions need to be changed over time - – Proactive Defragmentation for improved performance and scalability • Opportunistic placement reduces user wait time for access initially, but over time causes resource fragmentation due to changing application workloads – Resource fragmentation decreases scalability (VDs/core) and performance (user QoE), hence the VDC Net-Utility » Net-Utility is a overall user QoE measurement across the VDC – Reactive Migrations for increased resilience and sustained availability • Cyber-attacks or planned maintenance necessitate VD migrations without drastically affecting VDC Net-Utility • We have developed proactive and reactive placement schemes 9 M. Sridharan, P. Calyam, A. Venkataraman, A. Berryman, “Defragmentation of Resources in Virtual Desktop Clouds for Cost-Aware Utility-Optimal Allocation”, IEEE Conf. on Utility and Cloud Computing (UCC), 2011.
  • 10. Problem Context Summary • To use OpenFlow for dynamic resource placement of VD applications via an URB and accomplish: – Provisioning of non-IP VD application traffic flows between thin- client sites and data centers based on utility functions – Path selection and load-balancing of VD flows to ensure satisfactory user QoE of interactive applications (e.g., video playback) – Leveraging in-band instrumentation and measurement to gather performance intelligence on cross traffic impact affecting VD – Automated management and centralized network as well as measurement control 10
  • 11. Discussion Topics • User QoE Problem Context • Solution Approach and Results • “One more thing…” 11
  • 12. VIMAN Lab’s “VDC-Analyst” VD Provisioning and Placement GENI Slice Testbed for VDC Hosting • VDC-Analyst → GENI • Design & Development → Validation and design tuning • Large-scale simulations → Cloud deployment experiments 12
  • 13. VDC Architecture Data Center OpenFlow Switches Thin-clients Unified Resource Broker Connection Broker Marker Packet Handler Packet Capture OpenFlow Switch Flow tables Group Tables Data Plane Packet/Flow Inspector Routing Engine Thin-client Virtual Desktop Secure Channel User Applications Hypervisor Security Token RDP/PCoIP Server Active Directory RDP/PCoIP Client Load Balancing Control Plane Service Engine Measurement Plane System Provisioning File System Resource Optimization Secure Channel Control Plane OpenFlow Controller Measurement Engine Active Measurement Congestion Detection Fault Detection 13 P. Calyam, S. Rajagopalan, A. Selvadhurai, S. Mohan, A. Venkataraman, A. Berryman, R. Ramnath, “Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications”, IFIP/IEEE International Symposium on Integrated Network Management (IM), 2013 .
  • 14. OpenFlow Switch OpenFlow Controller Smart Thin-client Virtual Desktop Join OpenFlow network Install flow rules for marker packets Send marker packet to request virtual desktop Recognize and punt the marker packet Parse marker packet and install client/server flows Access virtual desktop applications Flow Setup Sequence Diagram for VD Placement 1 2 3 4 5 6 14
  • 15. VDC-Analyst Experiment w/o Load-Balancing 15
  • 16. VDC-Analyst Experiment w/ Load-Balancing 16
  • 17. OpenFlow Switch Client In Port Out Port SUNNW PG48 50 51 SUNNW PG49 50 51 ATLANTA PG46 52 52 ATLANTA PG47 52 52 ATLANTA PG46 20 52 ATLANTA PG47 20 52 VDC-Analyst OpenFlow Demonstration Route setupStep-1 Cross-traffic Impact Step-2 Load-balancing ImprovementStep-3 OpenFlow Switch Client In Port Out Port ATLA PG46 20 52 ATLA PG47 20 52 OpenFlow Switch Client In Port Out Port ATLANTA PG46 20 52 ATLANTA PG47 20 52 SUNNW PG48 50 52 SUNNW PG49 50 52 Video runs smooth, GUI applications are responsive Video freezes, disconnects, GUI applications are not responsive Video runs smooth, GUI applications are responsive 17
  • 18. 0.21 15.36 0 5 10 15 20 Application Cross-Traffic VDC-Analyst OpenFlow Demonstration Route setupStep-1 Cross-traffic Impact Step-2 Load-balancing ImprovementStep-3 Video runs smooth, GUI applications are responsive Video freezes, disconnects, GUI applications are not responsive Video runs smooth, GUI applications are responsive Bandwidth Consumed (Mbytes/s) 4.45 14.8 0 5 10 15 20 Application Cross-Traffic 4.6 0 0 5 10 15 20 Application Cross-Traffic 18
  • 19. Discussion Topics • User QoE Problem Context • Solution Approach and Results • “One more thing…” 19
  • 20. User QoE Degradation Troubleshooting • End-to-end user QoE degradation troubleshooting with OpenFlow over multi-domain Layer 2 networks 20 Slow-motion benchmarking of thin-client performance – VDBench Tool Real-time Capture and Analysis of Packet Traces of User Tasks (without using spanning ports)
  • 21. Thank you for your attention! 21

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