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Mobility Trace Generator. Fan Bai, Narayanan Sadagopan Computer Network Lab. Motivation. Currently, MANETs are not widely deployed Not much real life statistical data available Research focuses on simulation Simulation Parameters
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Mobility Trace Generator Fan Bai, Narayanan Sadagopan Computer Network Lab
Motivation • Currently, MANETs are not widely deployed • Not much real life statistical data available • Research focuses on simulation • Simulation Parameters • Mobility Pattern: usually, uniformly and randomly chosen destinations (random waypoint model) • Traffic Pattern: usually, uniformly and randomly communicating nodes
Ns-2 tcl script • Two input trace files • Mobility trace file • Default is /indep-utils/cmu-scen-gen/setdest/setdest • Format (interface): • $ns_ at <time> “$node_(<id>) setdest <x> <y> <speed>” • Traffic pattern file • Default is /indep-utils/cum-scen-gen/cbrgen.tcl
Motivation • Emerging MANETs will be deployed in myriad of scenarios with a rich set of network dynamics and mobility patterns • Impact of mobility on ad hoc routing protocols is expected to be significant • Many existing models (including random waypoint) fail to capture • Spatial dependence of movement among nodes • Temporal dependence of movement of a node over time • Existence of barriers or obstacles constraining mobility
Mobility Models Temporary Dependence Spatial Dependence Geographic Restriction Application Random Waypoint Model General No No No Group Mobility Model Battlefield No Yes No Freeway Mobility Model Metropolitan Traffic Yes Yes Yes Manhattan Mobility Model Metropolitan Traffic No Yes Yes
Random waypoint • Random Waypoint Model • Each node chooses a random destination and moves towards it with a random velocity chosen from [0, Vmax] • After reaching the destination, the node stops for a duration defined by the “pause time” parameter • After this duration, it again chooses a random destination and repeats the whole process again until the simulation ends • Parameters: Max Velocity Vmax, Pause time T
Setdest utility • Format • $node(<id>) set X_ <x0> • $node(<id>) set Y_ <y0> • $node(<id>) set Z_ <z0> • $ns_ at <time> “$node_(<id>) setdest <x> <y> <speed>” • Command • ./setdest –n <num_of_nodes> -p <pause_time> -s <max_speed> -t <simu_time> -x <max_x> -y <max_y> > <trace_filename>
Reference Point Group Mobility • Reference Point Group Model • Each group has a logical center (group leader) that determines the group’s motion behavior • Each nodes within group has a speed and direction that is derived by randomly deviating from that of the group leader • Parameter: • Angle Deviation Ratio(ADR) and Speed Deviation Ratio(SDR) • Max_velocity
Group Mobility Generator • In simulation, we use two sets of trace files • Single group: all nodes move within one group • Multiple group: each group moves independent of each other and in an overlapping fashion • Input • Mobility trace file of group leaders • Output • Mobility trace file of all nodes SG MG
Freeway Model • Freeway Model • 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
Implementation • Parameters • Map and Max_velocity • Input: map format • <freeway id> <lane id> <x0,y0> <x1,y1> • Output • Trace file for all nodes • Key • Link list to maintain the order of nodes on the same lane • Randomly insert the nodes into various lane
Manhattan Model • Similar specification with freeway, but it allows node to make turns at each corner of street • At each intersection • Probability of moving on the same street is 0.5 • Probability of turning right is 0.25 • Probability of turning left is 0.25 • Parameter • Map • Max_velocity
Manhattan Map • Input: map • Street: <street_id> <lane_id> <direction> <x0,y0> <x1,y1> • Corner: <ver_str_id> <hrn_str_id> <x,y>