1. Group #3: Mobility Models and Mobile Testbeds

2. The Models Motion, Traffic, Network

3. 3 Model Flexibility Multiple scale models –Micro and Macro levels e.g., from stop signs to cross town patterns –Both in time and in space Heterogeneous behavior –Node behavior is impacted by environment –Network characteristics are impacted by node behavior Multi-faceted scenarios –Combines motion, data traffic, map, infrastructure –Interrelation between data/motion; data caching; aggregation, etc

4. 4 Model Flexibility (cont) Trade off between accuracy and usability of the models –Different applications may focus on different parameters

5. 5 Traces to Models Traces: –Lack of cellular traces (owned by providers) –Lack of vehicular traces (not enough testbeds) –Lack of urban traces –Lack of social network tracing experiments Interplay/synergy of: –Measured traces –Synthetic models/traces –Theoretical motion/traffic models

6. 6 Metrics and Parameters Sensitivity analysis Impact on Data Performance Metrics –How are the metrics impacted by the particular motion patterns, etc –How do the motion patterns impact the traffic, etc Consider new network characteristics: –Inter-contact time (neighborhood change), partitioning, clustering, etc

7. 7 Performance Benchmarks Defined benchmarks Knobs, ie, flexibility –Need to understand effect of knobs –Need knobs tunable to applications Sound design methodology –Ability to tradeoff accuracy, complexity etc –Verifiability

8. 8 Evaluation Methodology Guidelines for community Model validation Model implementation verification Sound statistical analysis of results

9. Testbeds

10. 10 Testbed Flexibility Multi-layer vs. single layer testbeds Multi-user Heterogeneous (hardware, protocols, applications) Broad range of motion: –Pre-scheduled to controlled to spontaneous Repeatability Technology evolution –From small scale testbeds (motes) to large scale testbeds (vehicles) –Evaluate the evolution

11. 11 Scalability Testbed expansion with simulation and emulation Integration with real world networks and applications

12. 12 Testbed Realism Need more than what simulation gives you Need to understand –Realistic user behavior in reaction to motion, data etc –Realistic channel behavior –Real implementation/HW constraints –The limitations of your research on your testbed Uncover the –interactions between layers and inefficiencies –Incorrect common beliefs Cost, etc

13. 13 Measurement Methodology Guidelines for the community Validation of the model (motion, traffic, etc) Verification of the implementation Repeatability Sensitivity analysis Sound statistical analysis