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John Otto, Fabián Bustamante & Randall Berry EECS, Northwestern University.

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Presentation on theme: "John Otto, Fabián Bustamante & Randall Berry EECS, Northwestern University."— Presentation transcript:

1 John Otto, Fabián Bustamante & Randall Berry EECS, Northwestern University

2 Otto, Bustamante & Berry 2 Size- and power-unlimited mobile network platform –Infrastructure-less –Mobility facilitates rapid information dissemination Many promising applications –Traditional Internet access –Environmental sensing –Traffic advisory and driver safety Challenging environment –Rapidly changing topology –Network density depends on vehicular density Down the Block & Around the Corner

3 Otto, Bustamante & Berry 3 Live experimentation –Viable when a few nodes are enough –OK for a proof of concept –Not an option with 100’s of vehicles Simulation-based experimentation and its risks –No agreed-upon platform –Vehicular mobility Traces and models –Signal propagation Trading scalability and realism Down the Block & Around the Corner

4 Otto, Bustamante & Berry 4 Performance of the network stack’s physical layer defines the boundaries of a system’s ability … and your environment determines the performance of the physical layer How does this impact our applications’ performance? Signal propagation varies widely between open field and urban settings Down the Block & Around the Corner

5 Otto, Bustamante & Berry 5 Challenging assumptions –Kotz et al. (2004) Opportunistic connectivity –Ott & Kutscher (2004) –Wu et al. (2005) (multi-hop V2V) –Bychkovsky et al. (2006) –Hadaller et al. (2007) Varied environments –Singh et al. (2002) DSRC 5.9 GHz band –Taliwal et al. (2004) –Cheng et al. (2007) We focus on –Vehicle-to-vehicle (V2V) –Varied environments –Line-of-sight (LOS) versus non-LOS communication Down the Block & Around the Corner

6 Otto, Bustamante & Berry 6 Deterministic models –Free space and two-ray ground –Ideal LOS (and ground reflection) signal strengths Do not account for variations in environment Empirical models –Based on measurements taken in an environment –Ray Tracing 1 Requires detailed knowledge of the environment Incurs significant computational cost Does not scale –Probabilistic empirical model Two parameters used to describe the environment Typically a good compromise between realism, scalability 1 McKown & Hamilton. “Ray tracing as a design tool for radio networks.” Down the Block & Around the Corner

7 Otto, Bustamante & Berry 7 Parameters –Path Loss Exponent ( β ) : environment decay rate –Shadowing (σ dB ): variation due to obstacles Can complex environments be modeled using just two parameters? Down the Block & Around the Corner Free Space path loss Environment path loss Random variations (obstacles)

8 Otto, Bustamante & Berry 8 Characterize signal propagation in urban settings –Pick representative environments –Measure signal propagation in line of sight (LOS) and non-LOS (Around the Corner – ATC) settings Pick a signal propagation model, a good simulator, and a simple application –Free-space, probabilistic shadowing … –ns, GloMoSim, JIST/SWANS … Evaluate application-level impact of environment This work appeared in Proc. of ICDCS, 2009 Down the Block & Around the Corner

9 Otto, Bustamante & Berry 9 Overview of radio propagation models Experimental characterization of radio propagation in an urban setting (Chicago) –Measurement platform –Measured environments –Data analysis Understanding the impact of signal propagation parameters on application performance Conclusion Down the Block & Around the Corner

10 Otto, Bustamante & Berry 10 Set of equipped vehicles with –Soekris net machines, 256 MB memory, 1GB flash storage –Garmin GPS 18 USB for positioning –Ubiquiti Networks 2.4 GHz b/g –7 dBi 2.4 GHz omni-directional antenna Software –Linux ( kernel) –iperf (CBR UDP stream) –tcpdump Garmin GPS 18 USB Soekris net4801 running Linux 7 dBi omni- directional antenna Down the Block & Around the Corner

11 Otto, Bustamante & Berry 11 Measurement in representative environments & times Open field – Provides a baseline; no buildings or any other obstacles Suburban – Residential area with trees, cars and houses set back from the road with space between them Urban – Large and tall buildings, very close to the street, few gaps between buildings, etc Down the Block & Around the Corner Run experiments: Daytime (high traffic) At night (low traffic)

12 Otto, Bustamante & Berry 12 Down the Block & Around the Corner No traffic Path loss exponent stabilizes at 3.10 Line-of-Sight (LOS) Communication Same road Path loss exponent Distance (meters) β / σβ / σOpen FieldSuburbanUrban LOS3.10 / 3.23 ATC

13 Otto, Bustamante & Berry 13 Down the Block & Around the Corner No traffic Median path loss exponent = 3.29 Around the Corner (ATC) Communication Perpendicular roads Path loss exponent Distance from intersection (meters) Distance (meters) β / σβ / σOpen FieldSuburbanUrban LOS3.10 / 3.23 ATC3.29 / 3.35

14 Otto, Bustamante & Berry 14 Same roadPerpendicular roads Down the Block & Around the Corner β / σβ / σOpen FieldSuburbanUrban LOS3.10 / 3.23 ATC3.29 / 3.35

15 Otto, Bustamante & Berry 15 SuburbanOpen field Down the Block & Around the Corner β / σβ / σOpen FieldSuburbanUrban LOS3.10 / / 7.28 ATC3.29 / 3.35

16 Otto, Bustamante & Berry 16 SuburbanOpen Field Down the Block & Around the Corner β / σβ / σOpen FieldSuburbanUrban LOS3.10 / / 7.28 ATC3.29 / / 8.44

17 Otto, Bustamante & Berry 17 Same roadPerpendicular roads Down the Block & Around the Corner β / σβ / σOpen FieldSuburbanUrban LOS3.10 / / 7.28 ATC3.29 / / 8.44 At 50 meters apart, LOS and ATC β = 3.2 At 80 meters apart, LOS β = 3.1… but ATC β > 4 !

18 Otto, Bustamante & Berry 18 Urban Down the Block & Around the Corner β / σβ / σOpen FieldSuburbanUrban LOS3.10 / / / 9.15 ATC3.29 / / / non-LOS communication, higher path loss exponent due to diffraction, reflection 50 meters apart, in LOS > 100 meters apart, no communication possible

19 Otto, Bustamante & Berry 19 SuburbanUrban Down the Block & Around the Corner Can be 20 meters from intersection before observing PLE increase Distance of obstructions from the road: Suburban: wide front lawns Urban: narrow sidewalks Immediate increase in PLE after leaving intersection

20 Otto, Bustamante & Berry 20 Obstacles increase signal variability (shadowing parameter) –e.g. from σ = 3.23 in an open field to 9.15 in an urban setting Vehicular traffic degrades signal strength Overall, path-loss exponent is not significantly impacted –e.g. from 3.10 in an open field to 3.17 in an urban setting Transmit range reduced by 14% –Open field: 1070 m –Urban: 915 m –(predicted with model) Down the Block & Around the Corner

21 Otto, Bustamante & Berry 21 Path loss exponent varies significantly –e.g in an open field to 4.05 in an urban setting Transmit range reduced by 70% –Open field: 715 m –Urban: 208 m –(predicted with model) Non-LOS communication is possible –Reflection, diffraction –Gaps between buildings Distance of obstacles from road is a significant factor Down the Block & Around the Corner

22 Otto, Bustamante & Berry 22 Challenge assumption: one set of parameters is sufficient Experiments contradict this assumption –For complex environments (suburban, urban) –LOS vs. non-LOS (ATC) is a key factor in communication –So, we actually need at least two sets of parameters: LOS and non-LOS (ATC) What is the impact at the application layer? Use simulations to evaluate application performance under –Environments –Parameter settings (e.g. LOS, ATC) Down the Block & Around the Corner

23 Otto, Bustamante & Berry 23 Pick a signal propagation model, a good simulator, and a simple application Signal propagation model –Log-normal path loss with shadowing Sample application – Epidemic-based data dissemination –e.g. Communicating road (traffic) conditions –Push-based protocol, based on Vahdat & Becker (2000) 1.Beacon 2.Exchange digest 3.Send messages Application performance metric: Delivery latency –e.g. Lower latency gives fresher data and better detouring ability Down the Block & Around the Corner

24 Otto, Bustamante & Berry 24 For simple environments –LOS vs. ATC does not affect performance However… for complex environments –LOS performance much higher than ATC –Combining data sets does not give average performance We evaluate LOS&ATC –Switch between LOS and ATC parameters: same / different street –Gives expected intermediate performance –Compromise between scalability and realism Down the Block & Around the Corner

25 Otto, Bustamante & Berry 25 For simulation – JiST/SWANS++ –http://www.aqualab.cs.northwestern.edu/projects/swans++/http://www.aqualab.cs.northwestern.edu/projects/swans++/ For vehicular mobility – STRAW –Using real cities’ road maps Lights, signals, speed limits –IDM car-following –MOBIL lane-changing –http://sourceforge.net/projects/straw/http://sourceforge.net/projects/straw/ Parameters –Map: downtown Chicago (approximate Manhattan grid), 1.76 km 2 –Radio settings: match experiment configuration 26 dBm transmit power, 7 dBi antenna gain, 2 Mbps fixed data rate –150 vehicles –2 hour duration Down the Block & Around the Corner

26 Otto, Bustamante & Berry 26 Down the Block & Around the Corner LOS ATC In an open field, the locations of the communicating vehicles (in line-of-sight or not) have no performance impact Open field setting with traffic

27 Otto, Bustamante & Berry 27 Down the Block & Around the Corner LOS ATC In urban settings, around-the-corner parameters mean smaller transmit range, hence lower performance Urban setting β / σβ / σUrban LOS3.17 / 9.15 ATC4.05 / 10.74

28 Otto, Bustamante & Berry 28 Down the Block & Around the Corner LOS ATC Combined Averaging parameters – by combining datasets – doesn’t yield averaged performance Urban setting β / σβ / σUrban LOS3.17 / 9.15 ATC4.05 / Combined3.43 / Intermediate PLE, but increased shadowing

29 Otto, Bustamante & Berry 29 Down the Block & Around the Corner Urban setting LOS ATC LOS&ATC Using two parameter sets and relative vehicle position, select LOS or ATC parameters based on node position

30 Otto, Bustamante & Berry 30 Simple environments (open field) –One set of parameters is sufficient –No difference in performance between LOS and ATC parameters Complex environments (suburban, urban) –Using one set of parameters (LOS or ATC) is not sufficient –Combining LOS and ATC gives worse than expected performance –LOS&ATC approach gives the expected intermediate performance Possible extensions to LOS&ATC –Tolerance for distance from the intersection –Simulating heterogeneous environments on the same map –Utilizing LOS/ATC information at the protocol or application layers –… Down the Block & Around the Corner

31 Otto, Bustamante & Berry 31 LOS is a major factor of signal propagation characteristics in complex environments Accounting for LOS versus non-LOS has a significant impact on application-level performance LOS&ATC is a computationally scalable and more realistic approach for modeling complex environments Part of C3R, a project on urban environmental monitoring through vehicular networks, working towards –Ensuring sustainable urban growth –Participatory sensing with a mobile platform –Applications including traffic advisory, air quality and noise monitoring Down the Block & Around the Corner

32 Otto, Bustamante & Berry 32 Same roadPerpendicular roads Down the Block & Around the Corner With traffic, Increased β (3.31) and σ β / σβ / σOpen FieldSuburbanUrban LOS3.10 / 3.23 ATC3.29 / 3.35

33 Otto, Bustamante & Berry 33 UrbanOpen field Down the Block & Around the Corner β / σβ / σOpen FieldSuburbanUrban LOS3.10 / / / 9.15 ATC3.29 / / 8.44 Similar to suburban: larger variations in path loss exponent


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