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Contact-Based Mobility Metrics for Delay-Tolerant Ad Hoc Networking

Contact-Based Mobility Metrics for Delay-Tolerant Ad Hoc Networking. A. Khelil , P.J. Marrón, K. Rothermel MASCOTS, Sept 29 2005. Outline. Motivation Related Work Contact-Based Mobility (CBM) Metrics Statistical and Theoretical Analysis for Random Waypoint Uses of CBM Metrics Conclusion.

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Contact-Based Mobility Metrics for Delay-Tolerant Ad Hoc Networking

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  1. Contact-Based Mobility Metrics for Delay-Tolerant Ad Hoc Networking A. Khelil, P.J. Marrón, K. Rothermel MASCOTS, Sept 29 2005

  2. Outline • Motivation • Related Work • Contact-Based Mobility (CBM) Metrics • Statistical and Theoretical Analysis for Random Waypoint • Uses of CBM Metrics • Conclusion

  3. src dest-1 dest-2 Motivation • Mobile ad hoc network (MANET) • In MANETs mobility can be exploited • to increase the capacity of the network *) • to overcome network partitioning • New class of protocols and applications • Physical transport of messages (mobility-aided) • Tolerate higher E2E transmission delays (delay-tolerant) • Delay-tolerant protocols and appl. act on a large time-scale  Investigation of mobility on a large time-scale is crucial *) M. Grossglauser et al. “Mobility Increases the Capacity of Ad Hoc Networks” Trans. on Netw., 2002.

  4. Related Work • Existing mobility metrics • Velocity-based: e.g. speed, relative speed • Link-based: e.g. link change rate, link duration *) • Route-based: e.g. route change rate, route duration **) • Metrics defined for (non-delay-tolerant) ad hoc routing • Metrics model mobility instantaneously and do not support detection of mobility patterns a large time-scale *) J. Boleng et al. “Metrics to Enable Adaptive Protocols for Mobile Ad Hoc Networks” ICWN, 2002. **) N. Sadagopan et al. “Paths: Analysis of Path Duration Distributions in MANET and their Impact on Routing Protocols” Mobihoc, 2003.

  5. Outline • Motivation • Related Work • Contact-Based Mobility (CBM) Metrics • Methodology and Terminology • Metrics Definition • Statistical and Theoretical Analysis for Random Waypoint • Uses of CBM Metrics • Conclusion

  6. A B A B Methodology and Terminology (1) • Observation: Epidemiology uses contacts to model mobility of individuals • We use “contacts” between nodes to quantify the mobility on a large time-scale • Assumption: Nodes are uniquely identified (e.g. MAC addr.) • Definitions • Encounter between nodes n and m occurs if distance(n,m) <= com. range enm={n, m, tstart, duration} • Contact: cnm={enm} 2nd E 3rd E 1st E

  7. Methodology and Terminology (2) • Node manages a contact table for the “time of interest T” • Cn={cnm}: set of contacts of node n in T • En={enm}: set of encounters of node n in T time of interest T

  8. Def. of Contact-Based Mobility (CBM) Metrics • Node-centric vs. network-wide • Metrics • Avg. Encounter Frequency = ( = 1.4) • Encounter Rate = (= 7/40 encounters/s) • Contact Rate =(= 5/40 contacts/s) • Avg. Encounter Duration = • Avg. Contact Duration = = 5 = 7

  9. Outline • Motivation • Related Work • Contact-Based Mobility (CBM) Metrics • Statistical and Theoretical Analysis for Random Waypoint • Uses of CBM Metrics • Conclusion

  10. Area 1000m x 1000m Number of nodes N Population closed N ∈[30,300] + Simulation time Communication range T = 1800 s R = 100 m Mobility Model - speed - pause uniform in [0,2] s Random waypoint uniform in [0, Vmax ] Vmax∈ [3,30] m/s Simulation Parameters Area R + + + + + + + + + +

  11. Average Encounter Frequency • AEF is independent from node density • AEF increases with Vmax

  12. Average Encounter Rate | Average Contact Rate • Linear increase with node density • linear increase with Vmax • Linear increase with node density • Non linear increase with Vmax AER / ACR ≈ AEF

  13. Avg. Contact Duration | Avg. Encounter Duration • Independent from node density • Decreases with Vmax • Independent from node density • Decreases with Vmax ACD / AED ≈ AEF

  14. A A 2R avgSpeed * time = avgSpeed * time * 2R = Vmax / 2 Analytical Model for Random Waypoint

  15. Comparison Analytical & Simulation Results • Results are very comparable • Differences are due to - Spatial node distribution is not exactly uniform, since nodes are more likely to locate in the middle of movement area [Bettstetter] - Average nodal speed decreases over time [Yoon]

  16. Outline • Motivation • Related Work • Contact-Based Mobility (CBM) Metrics • Statistical and Theoretical Analysis for Random Waypoint • Uses of CBM Metrics • CBM Metrics in Network Simulator ns-2 • Conclusion

  17. src dest-1 Uses of CBM Metrics • Design and adaptation of delay-tolerant mobility-aided protocols • Detect large time-scale mobility patterns, examples: • Node src encounters dest-1 periodically • Nodes src and x move in a group • At run-time: HELLO beaconing x • Performance analysis of delay-tolerant mobility-aided protocols • Classification of mobility scenario • Performance evaluation and comparison

  18. The Network Simulator ns-2 • Ns-2: discrete event simulator for wired & wireless networks • General Operations Director (GOD): central instance • Stores global state information: • #nodes • node position • number of hops between 2 nodes • partitioning information • GOD simplifies (global view) evaluation of wireless protocols

  19. CBM Metrics in ns-2 Arbitrary ns-2 movement trace Basic communication model A and B communicate if distance(A,B) <= comm_range Before simulation Annotation Tool Movement trace annotated with CBM information ns-2 GeneralOperationsDirector(GOD) Delay- Tolerant Protocol Evaluation Query() During simulation Simulation trace CBM metrics http://canu.informatik.uni-stuttgart.de/cbm

  20. Conclusion • We introduced novel metrics to quantify mobility on a large time- scale • Based on contacts between nodes • Important for evaluation of mobility-aided delay-tolerant networking • Detailed statistical analysis for random waypoint • First steps towards an analytical model for random waypoint • We provide implementation for ns-2

  21. Thank you for your attention! http://canu.informatik.uni-stuttgart.de/cbm {khelil,marron,rothermel}@informatik.uni-stuttgart.de

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