1. Neighborhood Changing Rate: A Unifying Parameter to Characterize and Evaluate Data Dissemination Scenarios Institut Eurécom † Department of Mobile Communications Sophia Antipolis, France Jérôme Härri †, Biao Zhou ‡, Mario Gerla ‡, Fethi Filali †, Christian Bonnet † {haerri,filali,bonnet}@eurecom.fr {zhb,gerla}@cs.ucla.edu University of California ‡ Department of Computer Science Los Angeles, USA 4th IEEE/IFIP Wireless On demand Network Systems and Services (WONS) Obergurgl, Austria January 24th 2007

2. Härri et al.Neighborhood Changing Rate (NCR) 2 Agenda Data Dissemination in Mobile Ad Hoc Network NCR –Definition –Example –Justification The Mobeyes Protocol Performance Results Conclusion

3. Härri et al.Neighborhood Changing Rate (NCR) 3 Data Dissemination A single car has a packet to spread A car shares its packet with all vehicles reachable within its transmission range. Objective: Disseminating the packet throughout the network Example: Spreading factor: 2

4. Härri et al.Neighborhood Changing Rate (NCR) 4 Data Dissemination At each encounter, the more vehicles the car meets, the more efficient is the spreading factor. Example: Spreading factor: 5

5. Härri et al.Neighborhood Changing Rate (NCR) 5 Data Dissemination In order to reduce the broadcast storm effect, no relaying. Each car that receiving the set of data may in turn share it with any encountered vehicle. Best dissemination Strategy: At each encounter point, a single car with data shares it with a large set of vehicles. Group mobility does not help data dissemination, as in that case, a large set of cars containing data shares it with a potentially smaller set of vehicles. Data Dissemination Efficiency : Time needed to spread a given set of data to the entire network.

6. Härri et al.Neighborhood Changing Rate (NCR) 6 Data Dissemination The data dissemination efficiency in therefore dependant to a large set of parameters: –The rate a car encounters other neighbors. –The number of vehicles met that do not follow a similar trajectory. –…–… Objective: Define a single universal metric including all these parameters In other terms, data dissemination efficiency may depend on a Neighborhood Changing Rate

7. Härri et al.Neighborhood Changing Rate (NCR) 7 Agenda Data Dissemination in Mobile Ad Hoc Network NCR –Definition –Example –Justification The Mobeyes Protocol Performance Results Conclusion

8. Härri et al.Neighborhood Changing Rate (NCR) 8 Let’s define – : Sampling interval equal to the time needed for a node to move a distance equal to its transmission range – : Expected Neighbor entering node i’s neighborhood during the time interval – : Expected Neighbor leaving node i’s neighborhood during the time interval – : Node i’s nodal degree at time t. Then,

9. Härri et al.Neighborhood Changing Rate (NCR) 9 Example: The NCR of Car 1 as a function of time, with  t=1

10. Härri et al.Neighborhood Changing Rate (NCR) 10 Neighborhood Changing Rate (NCR) Definition (Uniform Mobility Model) : A Uniform Mobility Model (UMM) is a model preserving uniformly distributed velocities and densities Theorem : Defining speed av - representing and density av – representing the average node density both generated by an UMM, NCR has the following features 1.0 ≤ NCR(t) ≤ 1 2.NCR speed av 3.NCR density av Proof: See paper

11. Härri et al.Neighborhood Changing Rate (NCR) 11 Neighborhood Changing Rate (NCR) The performance of protocols using data dissemination usually depends on multiple criteria –Speed –Velocity –Mobility pattern –… Evaluating a protocol depending on multi-criteria is hard and gives arguable results. More specifically, Mobility Patterns are not easily quantifiable because they depend on a too large set of parameters. It would be preferable to evaluate it depending on a single criterion.

12. Härri et al.Neighborhood Changing Rate (NCR) 12 Neighborhood Changing Rate (NCR) As NCR is independent to speed av and density av,  In all models where the real speed and density diverge from the initial speed av and density av,  NCR controls the set of parameters that generates the complex spatial and temporal dependencies we may observe in realistic mobility patterns Specific Topologies or Mobility Patterns may become less relevant to evaluate the performance of dissemination protocols With a given speed av, density av, and NCR, we can perform cross-topology and cross-mobility patterns performance evaluation.

13. Härri et al.Neighborhood Changing Rate (NCR) 13 Neighborhood Changing Rate (NCR) A similar situation also exists in Transportation Planning: –How to represent traffic flows in transportation that depend on multi-parameters such as: Speed, density, volume/capacity ? –Level of Service (LOS) : Works like an American report card grade, using the letters A through F, with A being best and F being worst. –By using LOS classification and referring to a traffic situation as having a particular LOS, engineers can have a global knowledge of traffic condition in a particular area. NCR is designed to have the same usage: –By referring to data dissemination as having a particular NCR, we can have an intuitive vision of its efficiency, and thus evaluate accurately VANET Protocols using this feature.

14. Härri et al.Neighborhood Changing Rate (NCR) 14 Agenda Data Dissemination in Mobile Ad Hoc Network NCR –Definition –Example –Justification The Mobeyes Protocol Performance Results Conclusion

15. Härri et al.Neighborhood Changing Rate (NCR) 15 The Mobeyes Protocol Mobeyes [1] is a protocol for sensed data mining in vehicular environments: –Periodic diffusion of a summary of sensed data –On demand harvesting of sensed data Mobeyes Architecture –Mobeyes Sensing Interface (MSI) : Interface responsible for the access to the sensors or GPS –Mobeyes Data Processor (MDP): Reads raw data and generates the summaries –Mobeyes Diffusion/Harvesting Processor (MDHP): Opportunistically diffuses the summaries or on demand harvests the raw data. Mobeyes uses epidemic dissemination to diffuse the summaries. So, it is an appropriate choice to validate NCR. [1] Uichin Lee et al. University of California, PerSeNS 2006

16. Härri et al.Neighborhood Changing Rate (NCR) 16 The Mobeyes Protocol Example: Mobeyes Single Hop Passive Diffusion

17. Härri et al.Neighborhood Changing Rate (NCR) 17 Agenda Data Dissemination in Mobile Ad Hoc Network NCR –Definition –Example –Justification The Mobeyes Protocol Performance Results Conclusion

18. Härri et al.Neighborhood Changing Rate (NCR) 18 Simulation Results Data Dissemination Protocol Mobeyes SimulatorNS-2.27 Hello Intervals3[s] Data Generation intervals 10’000[s] Simulation time2000[s] Simulation Area2400[m] x 2400[m] Number of Nodes100 Tx Range250[m] Speed5[m/s], 15[m/s], 25[m/s] Simulation Parameters Simulation Environment Urban Map TopologyTriangle Topology 760m 2400m

19. Härri et al.Neighborhood Changing Rate (NCR) 19 Mobility Models Track ModelRandom Waypoint Model [1] Biao Zhou et al. University of California, MilCom 2004

20. Härri et al.Neighborhood Changing Rate (NCR) 20 Latency Latency on a Triangle Topology as a function of speed

21. Härri et al.Neighborhood Changing Rate (NCR) 21 Latency Latency on a Map Topology as a function of speed

22. Härri et al.Neighborhood Changing Rate (NCR) 22 Harvesting Efficiency NCR on a Triangle Topology with a speed of 5 m/s

23. Härri et al.Neighborhood Changing Rate (NCR) 23 Harvesting Efficiency NCR on a Triangle Topology with a speed of 15 m/s

24. Härri et al.Neighborhood Changing Rate (NCR) 24 Harvesting Efficiency NCR on a Triangle Topology with a speed of 25 m/s

25. Härri et al.Neighborhood Changing Rate (NCR) 25 Harvesting Efficiency Mobeyes on a triangle topology:  Time before which 100% of the data is harvested HighMediumLow 5 m/s 75.08 s102.58 s181.89 s 15 m/s 50.27 s55.97 s77.41 s 25 m/s 38.1 s47.23 s49.08 s velocity av NCR

26. Härri et al.Neighborhood Changing Rate (NCR) 26 Harvesting Efficiency NCR on a Map Topology with a speed of 5 m/s

27. Härri et al.Neighborhood Changing Rate (NCR) 27 Harvesting Efficiency NCR on a Map Topology with a speed of 15 m/s

28. Härri et al.Neighborhood Changing Rate (NCR) 28 Harvesting Efficiency NCR on a Map Topology with a speed of 5 m/s

29. Härri et al.Neighborhood Changing Rate (NCR) 29 Harvesting Efficiency Mobeyes on a map topology:  Time before which 100% of the data is harvested HighMediumLow 5 m/s 1986.3 s>> 2000s 15 m/s 1344 s1548.5 s>> 2000s 25 m/s 1093.1 s1246.1 s1610.7 s velocity av NCR

30. Härri et al.Neighborhood Changing Rate (NCR) 30 Harvesting Efficiency Mobeyes on a map topology:  Time before which 100% of the data is harvested HighMediumLow 5 m/s 86.36s>> 87s 15 m/s 58.43s67.32s>> 87s 25 m/s 47.52s54.18s70.03s velocity av NCR

31. Härri et al.Neighborhood Changing Rate (NCR) 31 Cross-Topology Comparison Latency for scenarios with same speed, density and NCR, and for different mobility models and topologies

32. Härri et al.Neighborhood Changing Rate (NCR) 32 Cross-Topology Comparison Harvesting rate for scenarios with same density, speed and NCR, and different mobility models and topologies

33. Härri et al.Neighborhood Changing Rate (NCR) 33 Cross-Topology Comparison All Models having the same NCR  Time before which 100% of the data is harvested Mobeyes + Map Mobeyes + Triangle RWM + Triangle 15 m/s 58.43s50.26s61.58 s velocity av topology

34. Härri et al.Neighborhood Changing Rate (NCR) 34 Conclusion NCR is a novel parameter describing data dissemination NCR is able to describe spatial and temporal dependencies, not covered by speed or density. NCR is an unifying parameter, as it regroup mobility patterns and topology parameters. Data dissemination in any kind of topology and for any type of mobility pattern, can be the fully control by three parameters: –Average Speed –Average Density –NCR

35. Härri et al.Neighborhood Changing Rate (NCR) 35 Questions ? Jérôme Härri haerri@eurecom.fr