diverse mobility patterns in mobile ad hoc network
TRANSCRIPT
Introduction Mobile Ad Hoc Networks (MANETs)
Formed by wireless mobile nodes Do not rely on any existing infrastructure Routes between mobile nodes are typically
multi-hop Network topology can be highly dynamic
Ad hoc routing protocols Reactive protocols: AODV, DSR Proactive protocols: DSDV Hybrid protocols: ZRP
Mobility Models
mobility model
deterministic modelrandom model hybrid model
predefined movementpath or real mobility trace
movement bounded by environmental constraints
arbitrary movement without constraints
Motivation
most of MANET simulations based on random mobility models, e.g. random waypoint model
• random models insufficient to reflect the environmental constraints
• deterministic mobility models too complex and real user traces hard to obtain
In some real situation, we need hybrid model such as RPGM
RPGM Reference Point Group Mobility Model
Logical relationship between nodes Group motion represented by “virtual center” Motion of reference point Relative random motion around reference point
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Parameters: Angle Deviation Ratio(ADR) and Speed Deviation Ratio(SDR), number of groups, max velocity Vmax.
Parameterized Mobility Model Freeway Model (FW)
Each mobile node is restricted to its lane on the freeway
The velocity of mobile node is temporally dependent on its previous velocity
If two mobile nodes on the same freeway lane are within the Safety Distance (SD), the velocity of the following node cannot exceed the velocity of preceding node
Parameter: Map layout, Vmax Manhattan Model (MH)
Similar to Freeway model, but it allows node to make turns at each corner of street
Parameter: Map layout, Vmax
Map for FW
Map for MH
Performance Metrics Relative Speed (mobility metric I)
The magnitude of relative speed of two nodes, average over all neighborhood pairs and all time
Spatial Dependence (mobility metric II) The value of extent of similarity of the velocities of two nodes that are not too far
apart, average over all neighborhood pairs and all time
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Average link duration (connectivity metric I) The value of link duration, average over all nodes pairs
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Mobility Metrics Objective:
validate whether proposed mobility models span the mobility space we explore
Relative speed For same Vmax, MH/FW is
higher than RWP, which is higher than SG/MG
Spatial dependence For SG/MG, strong degree of
spatial dependence For RWP/FW/MH, no obvious
spatial dependence is observed
Relative Speed
Spatial Dependence
Connectivity Graph Metrics Link duration
For same Vmax, SG/MG is higher than RWP, which is higher than FW, which is higher than MH
Summary Freeway and Manhattan model
exhibits a high relative speed Spatial Dependence for group
mobility is high, while it is low for random waypoint and other models
Link Duration for group mobility is higher than Freeway, Manhattan and random waypoint Link duration
Performance Comparison Performance of routing protocols may vary drastically across
mobility patterns Eg : DSR
There is a difference of 40% for throughput and an order of magnitude difference for routing overhead by mobility models!
Throughput Routing Overhead
Throughput vs. Protocols
Random Waypoint : DSR? Manhattan : AODV or DSR?
We observe that using different mobility models may alter the ranking of protocols in terms of the throughput!
Overhead vs. Protocols
RPGM(single group) : DSR? Manhattan : DSDV?
We observe that using different mobility models may alter the ranking of protocols in terms of the routing overhead!
Conclusion: Mobility DOES matter, significantly, in evaluation of protocol performance and in comparison of various protocols!
Analysis of the results Recall: If mobility affects protocol performance, why? We observe a very clear trend between mobility metric,
connectivity and performance With similar average spatial dependency
Relative Speed increases Link Duration decreases Routing Overhead increases and throughput decreases
With similar average relative speed Spatial Dependence increase Link Duration increases
Throughput increases and routing overhead decreases Conclusion: Mobility Metrics influence
Connectivity Metrics which in turn influence protocol performance metrics !
Put all the pieces togetherRelative Velocity
Spatial Dependence
Link Duration
Throughput
Overhead
Conclusion Researched protocol independent metrics to
capture a few mobility characteristics of interest and compared a rich set of mobility models
Evaluated protocols over mobility models that span the above mobility characteristics
Performance trends and comparison results vary widely with the choice of mobility
Understood the logical relationship between mobility and protocol performance
Mobility patterns are IMPORTANT
Future Work To extend mobility pattern to multicast
protocols. MAODV Geocast Protocols
To analyze the reason of effect of diverse mobility pattern
Reference [1] N.Sadagopan, F.Bai, B.Krishnamachari,
A.Helmy, “PATHS: analysis of PATH duration Statistics and their impact on reactive MANET routing protocols” MobiHoc 2003.
[2] F.Bai, N.Sadagopan, A.Helmy, “BRICS: A Building-block approach for analyzing RoutIng protoCols in ad hoc networkS- a case study of reactive routing protocols”, USC-CS-TR-02-775, in submission.
[3] http://www-scf.usc.edu/~fbai/mobility.html