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Gain More for Less: The Surprising Benefits of QoS Management in Constrained NDN Networks ACM ICN 2019, Macau Cenk Gndoan 1 Jakob Pfender 2 Michael Frey 3 Thomas C. Schmidt 1 Felix Shzu-Juraschek 3 Matthias Whlisch 4 1 HAW Hamburg 2 Victoria


  1. Gain More for Less: The Surprising Benefits of QoS Management in Constrained NDN Networks ACM ICN 2019, Macau Cenk Gündoğan 1 Jakob Pfender 2 Michael Frey 3 Thomas C. Schmidt 1 Felix Shzu-Juraschek 3 Matthias Wählisch 4 1 HAW Hamburg 2 Victoria University of Wellington 3 Safety IO 4 Freie Universität Berlin

  2. Common IoT Deployments ◮ Always connected, low-cost IoT devices ◮ Resource-constrained: MHz CPU, kB RAM/ROM 2 / 39

  3. Common IoT Deployments ◮ Always connected, low-cost IoT devices ◮ Resource-constrained: MHz CPU, kB RAM/ROM ◮ Saturated resources impact network performance ◮ Local bottlenecks leave the network partially underutilized 3 / 39

  4. Common IoT Deployments ◮ Always connected, low-cost IoT devices ◮ Resource-constrained: MHz CPU, kB RAM/ROM ◮ Saturated resources impact network performance ◮ Local bottlenecks leave the network partially underutilized ◮ Overprovisioning of resources to meet requirements ... 4 / 39

  5. Common IoT Deployments ◮ Always connected, low-cost IoT devices ◮ Resource-constrained: MHz CPU, kB RAM/ROM ◮ Saturated resources impact network performance ◮ Local bottlenecks leave the network partially underutilized ◮ Overprovisioning of resources to meet requirements ... is infeasible ◮ Device complexity, unit price, and energy consumption increases 5 / 39

  6. Common IoT Deployments ◮ Always connected, low-cost IoT devices ◮ Resource-constrained: MHz CPU, kB RAM/ROM ◮ Saturated resources impact network performance ◮ Local bottlenecks leave the network partially underutilized ◮ Overprovisioning of resources to meet requirements ... is infeasible ◮ Device complexity, unit price, and energy consumption increases Quality of Service (QoS) improves resource utilization 6 / 39

  7. Outline Resources in IP vs. NDN Distributed QoS Management Experimental Evaluation Conclusion & Outlook 7 / 39

  8. Resources in IP vs. NDN ◮ Typical IP world resources: link capacities & buffer spaces IP Resources Forwarding Queues 8 / 39

  9. Resources in IP vs. NDN ◮ Typical IP world resources: link capacities & buffer spaces ◮ CCNx / NDN provides additional resources: Pending Interest Table (PIT) , Content Store (CS) IP Resources PIT CS Forwarding Queues NDN Resources 9 / 39

  10. Distributed QoS Management

  11. QoS Building Blocks 1. Traffic classification 2. QoS treatments 11 / 39

  12. QoS Building Blocks 1. Traffic classification ◮ Longest prefix match (LPM) with pre-defined name ↔ priority table ◮ Alternatively: draf-moiseenko-icnrg-flowclass, I. Moiseenko and D. Oran 2. QoS treatments 12 / 39

  13. QoS Building Blocks 1. Traffic classification ◮ Longest prefix match (LPM) with pre-defined name ↔ priority table ◮ Alternatively: draf-moiseenko-icnrg-flowclass, I. Moiseenko and D. Oran 2. QoS treatments ⇐ focus of this talk ◮ Define quality dimensions ◮ Specify resource management rules 13 / 39

  14. Quality Dimensions � Reliable, Prompt � � Reliable, Regular � Toxic gas alerts Reliability in underground mines � Regular, Prompt � � Regular, Regular � Temperature readings in a class room Latency 14 / 39

  15. Resource Management Rules 3. Distributed Coordination 1. Isolated Decisions 2. Resource Correlations PIT Coherence Forwarding Queue CS—PIT Correlation Same config. at all nodes Delay regular traffic Prompt Data meets no PI ⇒ cached with priority ⇒ Regular < Reliable < Prompt Pending Interest Table CS Efficiency Evict regular for prompt CS—Forward. Correlation Same config. at all nodes Prompt Data dropped Content Store ⇒ cached with priority ⇒ Regular < Prompt < Reliable Evict regular for reliable 15 / 39

  16. Resource Management Rules 3. Distributed Coordination 1. Isolated Decisions 2. Resource Correlations PIT Coherence Forwarding Queue CS—PIT Correlation Same config. at all nodes Delay regular traffic Prompt Data meets no PI ⇒ cached with priority ⇒ Regular < Reliable < Prompt Pending Interest Table CS Efficiency Evict regular for prompt CS—Forward. Correlation Same config. at all nodes Prompt Data dropped Content Store ⇒ cached with priority ⇒ Regular < Prompt < Reliable Evict regular for reliable 16 / 39

  17. Resource Management Rules 3. Distributed Coordination 1. Isolated Decisions 2. Resource Correlations PIT Coherence Forwarding Queue CS—PIT Correlation Same config. at all nodes Delay regular traffic Prompt Data meets no PI ⇒ cached with priority ⇒ Regular < Reliable < Prompt Pending Interest Table CS Efficiency Evict regular for prompt CS—Forward. Correlation Same config. at all nodes Prompt Data dropped Content Store ⇒ cached with priority ⇒ Regular < Prompt < Reliable Evict regular for reliable 17 / 39

  18. Resource Management Rules 3. Distributed Coordination 1. Isolated Decisions 2. Resource Correlations PIT Coherence Forwarding Queue CS—PIT Correlation Same config. at all nodes Delay regular traffic Prompt Data meets no PI ⇒ cached with priority ⇒ Regular < Reliable < Prompt Pending Interest Table CS Efficiency Evict regular for prompt CS—Forward. Correlation Same config. at all nodes Prompt Data dropped Content Store ⇒ cached with priority ⇒ Regular < Prompt < Reliable Evict regular for reliable 18 / 39

  19. Experimental Evaluation

  20. Experimental Evaluation Setup Hardware: M3 Node in IoT Lab testbed Sofware: RIOT with CCN-lite Network: Multi-hop topology with 31 nodes Gateway M3 Node (ARM Cortex-M3) 64 kB RAM / 512 kB ROM 802.15.4 radio transceiver 20 / 39

  21. Scenario Descriptions Mixed Sensors and Actuators Sensing and Lighting Control 21 / 39

  22. Scenario Descriptions Mixed Sensors and Actuators ◮ Gateway requests device-specific temperature readings every 10 s ± 2 s Sensing and Lighting Control Gateway Traffic Interest 22 / 39

  23. Scenario Descriptions Mixed Sensors and Actuators ◮ Gateway requests device-specific temperature readings every 10 s ± 2 s ◮ Actuators request device-specific state from gateway every 5 s ± 1 s Sensing and Lighting Control Gateway Traffic Actuators Traffic Interest Interest 23 / 39

  24. Scenario Descriptions Mixed Sensors and Actuators ◮ Gateway requests device-specific temperature readings every 10 s ± 2 s ◮ Actuators request device-specific state from gateway every 5 s ± 1 s Sensing and Lighting Control ◮ Actuators request group-specific instructions from gateway every 5 s ± 1 s Gateway Traffic Actuators Traffic Interest Interest cache hit cache hit 24 / 39

  25. Evaluation Metrics Success Throughput Latency 25 / 39

  26. Evaluation Metrics: Success Rates Success Throughput Latency 26 / 39

  27. Nodal Success Rates for Actuators Traffic Success Rate [%] 0 20 40 100 60 80 Regular 27 / 39

  28. Nodal Success Rates for Actuators Traffic Success Rate [%] 0 20 40 100 60 80 Regular QoS Coordinated 28 / 39

  29. Overall Success Rates Sensing & Lighting Control Mixed Sensors & Actuators Regular QoS Coordinated Regular QoS Coordinated 100 12 Actuators 10 8 80 6 Success Rate [%] 4 Rank [Hops] 60 2 12 40 10 8 6 20 Gateway 4 2 0 5 10 15 20 25 30 5 10 15 20 25 30 5 10 15 20 25 30 5 10 15 20 25 30 PIT Size [Maximum # of Entries] CS Size [Maximum # of Entries] 29 / 39

  30. Overall Success Rates Sensing & Lighting Control Mixed Sensors & Actuators Regular QoS Coordinated Regular QoS Coordinated 100 12 Actuators 10 8 80 6 Success Rate [%] 4 Rank [Hops] 60 2 12 40 10 8 6 20 Gateway 4 2 0 5 10 15 20 25 30 5 10 15 20 25 30 5 10 15 20 25 30 5 10 15 20 25 30 PIT Size [Maximum # of Entries] CS Size [Maximum # of Entries] 30 / 39

  31. Overall Success Rates Sensing & Lighting Control Mixed Sensors & Actuators Regular QoS Coordinated Regular QoS Coordinated 100 12 Actuators 10 8 80 6 Success Rate [%] 4 Rank [Hops] 60 2 Cache Hit [%] Regular QoS Coordinated 12 40 40 10 20 8 6 20 Gateway 0 4 CS5 CS15 CS30 2 0 CS Size [Maximum # of Entries] 5 10 15 20 25 30 5 10 15 20 25 30 5 10 15 20 25 30 5 10 15 20 25 30 PIT Size [Maximum # of Entries] CS Size [Maximum # of Entries] 31 / 39

  32. Evaluation Metrics: Throughput Evolution Throughput Success Latency 32 / 39

  33. Throughput Evolution for Unprioritized Traffic Regular QoS Coordinated 600 Outgoing Interests 400 w/o Actuator Traffic w/ Actuator Traffic w/o Actuator Traffic w/ Actuator Traffic 200 min ] Packets [ # 0 600 400 w/o Actuator Traffic w/ Actuator Traffic w/o Actuator Traffic w/ Actuator Traffic Incoming 200 Data 0 5 10 15 20 5 10 15 20 Duration [min] 33 / 39

  34. Throughput Evolution for Unprioritized Traffic Regular QoS Coordinated 600 Outgoing Interests 400 w/o Actuator Traffic w/ Actuator Traffic w/o Actuator Traffic w/ Actuator Traffic 200 min ] Packets [ # 0 600 400 w/o Actuator Traffic w/ Actuator Traffic w/o Actuator Traffic w/ Actuator Traffic Incoming 200 Data 0 5 10 15 20 5 10 15 20 Duration [min] 34 / 39

  35. Goodput Evolution Regular QoS Coordinated 6 Gateway 4 2 PIT5 PIT30 min ] Goodput [ KiB 0 0 5 10 15 0 5 10 15 Duration [min] 0 . 6 PIT5 PIT30 PIT5 PIT30 0 . 4 Actuators 0 . 2 0 2 4 10 12 2 4 10 12 2 4 10 12 2 4 10 12 6 8 6 8 6 8 6 8 Rank [Hops] 35 / 39

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