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Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Stochastic Characterization of Mobile Ad-hoc Networks John P. Mullen and Timothy I. Matis Center for Stochastic Modeling Department of Industrial Engineering New Mexico State University INFORMS 2004
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2 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 What Are MANETS ? A MANET is a mobile ad-hoc wireless communication network that is capable of autonomous operation Each node is capable of transmitting, receiving, and routing packets of information. The network has no fixed backbone The nodes are able to enter, leave, and move around the network independently and randomly
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3 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Mobile Ad Hoc Path Search Y X A B I G E F C D H
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4 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Same MANET After a While Y X A B I G E F C D H H X I G F E D B A C Y
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5 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Nutshell MANET field performance differs greatly from simulation’s Field & testbed performance is much poorer Developing MANET protocols in the field is very difficult Improving simulation fidelity increases the value of simulation in design. Higher fidelity earlier in the design process leads to better designs Research focus: Significantly improve the fidelity of MANET simulations Without significantly increasing Simulation run time or Modeling effort. Research results Up to an order of magnitude improvement in fidelity Runtime increases are often insignificant, but generally less than 100% Very little added modeling effort
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6 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Overview Multipath Fading and its impact on mobile ad hoc nets The Stochastic Model Objectives Implementation Validation Demonstrations of the Model Small Models Impact of Short Retry Limit (SRL) Comparing AODV and DSR Large Models AODV vs. DSR AODV vs. DSR using GPS data Impact of SRL on DSR Summary, Conclusions and Further Work
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7 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Shadowing and Fading Shadowing Is caused by objects absorbing part of the signal Can be estimated by looking at the Line of Sight (LOS) path Causes a random reduction in signal strength. Fading Is the result of the algebraic sum of signals from many paths Because movement of any object in the vicinity can change the sum Multipath fading is extremely difficult to model and predict Would be very time consuming to simulate exactly And would have little predictive value. This phenomena causes: Very rapid large-scale fluctuations in signal strength Can cause the signal to be significantly lesser or greater than expected.
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8 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Main causes of signal variation R T Shadowing Multipath
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9 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Measured Received Signal Strength (from Neskovic 2000)
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10 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Stochastic Variation Model The Model Given m p (d), the expectation of power at distance d Rayleigh fading model of the instantaneous power, P(d) Pr {P(d) ≤ p} = 1 – exp{-[p/m p (d)]} Inverse transform of the Rayleigh fading model P(d) = -m p (d)ln(1-r)
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11 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Simulated vs. Real Power Actual Measurements Simulated Values
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12 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Validation Simulated reported field tests and compared results K.-W. Chin, J. Judge, A. Williams, and R. Kermode, "Implementation experience with MANET routing protocols," ACM SIGCOMM Computer Communications Review, vol. 32, pp. 49 - 59, 2002. I. D. Chakeres and E. M. Belding-Royer, "The Utility of Hello messages for determining link connectivity," Wireless Personal Multimedia Communications, vol. 2, pp. 504 - 508, 2003. D. S. J. D. Couto, D. Aguayo, J. Bicket, and R. Morris, "A High Throughput Path Metric for MultiHop Wireless Routing," presented at MobiCom '03, San Diego, California, USA, 2003. S. Desilva and S. Das, "Experimental evaluation of a wireless ad hoc network," 2000. Simulations with Standard non-fading model were exceedingly optimistic Proposed fading model were very much more realistic.
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13 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Impact of Multipath Fading on MANETs How does it affect MANETs? Unnecessary route searches Selection of false routes
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14 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Impact of Multipath Fading On MANETs Nominal Range (r 0 ) OK Stub Cellular Dropped Packets Fading margin False Routes OK
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15 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Impact of Multiple Retries on MANETs
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16 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 The MANET fading Trade-off Protocol Improve Reliability On Good Routes Increase Risk of Selecting Bad Routes MANET: Nominal range is a matter of balance. Most Wireless: Nominal range is a matter of design.
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17 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Demonstrations Small Models (validations of field tests) Scenario 1 – Performance vs. distance. Used for the two cases above Scenario 2 – Routing Test Focus mainly on fading effects Models: Fading vs. nonfading simulations of AODV DSR vs. AODV with fading model Large models (exploration) Scenario 3 – 24 nodes. Also consider other effects, such as interference Models: Fading and non-fading versions of AODV vs. DSR AODV vs. DSR using GPS data Impact of SRL on DSR
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18 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Scenario 2: Routing test (from Chin et. al., 2002) 10 pps 0.5 m/s r 0 = 39m
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19 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Sc 2: Fading vs. Nonfading: AODV Notes: Default values for AODV SRL = 7
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20 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Sc 2: AODV vs. DSR Notes: Default protocol values SRL = 7 Nonfading model shows no difference
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21 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Scenario 3: Larger Scale Test Features: More nodes (24) Random r-t pairs Interference Higher loads
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22 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Mean Throughput: AODV vs. DSR Notes: Default protocol values SRL = 7
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23 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Mean Delay: AODV vs. DSR Notes: Default protocol values SRL = 7
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24 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Using GPS data 3 2 1 B A r0r0 Use GPS to block unreliable routes
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25 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Impact of GPS Without GPS With GPS
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26 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Mean Throughput: Impact of SRL on DSR Notes: Default protocol values
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27 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Mean Delay: Impact of SRL on DSR Notes: Default protocol values
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28 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Execution Time in Scenario 3 (Virtually no differences in Scenarios 1 & 2)
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29 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Summary Non fading model Overestimates field performance Is very insensitive to all the contrasts shown here and more. Fading model Provides more realistic estimates Better predicts impacts of protocol and parameter changes Shows promise of new techniques. Requires little or no additional modeling Has little impact on execution time (Alternative is a testbed or a field trial)
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30 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Conclusions Multipath Fading has a great impact on mobile ad hoc nets Including its effects in simulation greatly improves fidelity Stochastic Modeling of Multipath Fading Is a practical way to include the impact of fading Minor modifications to code (in OPNET, at least) Without great increases in Modeling effort or Execution time
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31 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Future Work More Fading Models Rayleigh Ricean Nakagami Other significant RF effects e.g. exponential decay factor Better user interface Allow selection of models & parameters without need to recompile. Validation Replicating published studies Set up own testbed and field trials Better modeling of fading impacts Hello vs. control vs. data packet results Other significant measurable elements.
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32 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Acknowledgements OPNET Technologies Software license research grant Technical assistance Center for Stochastic Modeling Technical resources Klipsch School of Electrical and Computer Engineering Dr. Steve Horan Dr. Hong Huang (also CSM member)
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33 INFORMS 2004 Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004 Final Questions?
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