how (not) to simulate wireless networks with ns brad karp [email protected] university college...

How (not) to SimulateWireless Networks with ns

Brad [email protected]

University College London

ns WorkshopMSR Cambridge

9th December, 2005

2

Outline

• Overview of ns wireless functionality– History– Simple example– MobileNode configuration– Controlling mobility– Defining traffic workloads– MobileNode architecture– Trace file format

• Role of simulation in wireless research• Case study of simulation’s pitfalls: GPSR

ns overview material largely borrowed:ns Manual (Chapter 16)Padma Haldar’s tutorial (11/2002)

3

History of ns Wireless Support

• David Johnson’s Monarch group at CMU:– Free-space, two-ray ground reflection channel

model– 802.11 MAC layer– Random waypoint mobility model– ARP– Ad hoc routing: Dynamic Source Routing (DSR),

TORA, …– &c.

• Other major supported protocols and links (outside scope of today’s talk): Mobile IP, Directed Diffusion, satellite links, &c.

4

ns Wireless Architecture

• MobileNode at core of mobility support• MobileNodes can move in a given

topology, receive/transmit signals to/from wireless channels

• Wireless network stack consists of LL, ARP, MAC, IFQ, &c.

• Allows simulations of multi-hop ad hoc networks, wireless LANs, sensor networks etc

5

Wireless Example:Ad hoc Routing

• Scenario– 2 mobile nodes– moving within 500m x 500m flat topology– using DSDV ad hoc routing protocol– Random Waypoint mobility model– TCP traffic

• Examples:– ns-2/ns-tutorial/examples/simple-

wireless.tcl– ns-2/tcl/ex/wireless-demo-csci694.tcl

6

An Example – Step 1

# Define Global Variables# create simulatorset ns [new Simulator]

# create flat topology in 670m x 670m areaset topo [new Topography] $topo load_flatgrid 500 500

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# Define wireless ns trace

# ns trace

set tracefd [open simple.tr w]

$ns trace-all $tracefd

8

GOD (General Operations Director)

• Stores all-pairs Dijkstra shortest path lengths

• Allows comparison of path length with optimal

• Automatically generated, contained in scenario file

• set god [create-god <no of mnodes>]• $god set-dist <from> <to> <#hops>

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Example –Step 3

• Create godset god [create-god 2]$ns at 900.00 “$god setdist 1 2 1”

• Create wireless channelset thechan [new

Channel/WirelessChannel]

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# Define how a mobile node is configured$ns node-config \

-adhocRouting DSDV \-llType LL \-macType Mac/802_11 \-ifqLen 50 \-ifqType Queue/DropTail/PriQueue \-antType Antenna/OmniAntenna \-propType Propagation/TwoRayGround \-phyType Phy/WirelessPhy \-channel $thechan \-topoInstance $topo-agentTrace ON \-routerTrace OFF \-macTrace OFF \-movementTrace OFF

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An Example – Step 5# Use “for” loop to create 3 nodes:

for {set i 0} {$i < 2} {incr i} {

set node($i) [$ns node]

# disable random motion

$node($i) random-motion 0

}

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MobileNode Movement

• Node position defined in 3D• Today, z axis not used

$node set X_ <x1>$node set Y_ <y1>$node set Z_ <z1>$node at <time> setdest <newx> <newy> <speed>

• Lots of these events over a simulation; manual generation tedious…

13

Random Waypoint Model

• Place nodes uniformly at random• Node moves to uniformly randomly

chosen destination, at velocity chosen uniformly at random

• Between move events, node stays put for “pause time”

• Meant to mimic user behavior: move, work, move…

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Scenario Generator: Movement

• setdest: MobileNode movement generatorsetdest -n <num_of_nodes> -p setdest -n <num_of_nodes> -p pausetime -M <maxspeed> -t pausetime -M <maxspeed> -t <simtime> -x <maxx> -y <maxy><simtime> -x <maxx> -y <maxy>

Source: ns-2/indep-utils/cmu-scen-ns-2/indep-utils/cmu-scen-gen/setdest/gen/setdest/

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Example setdest Output

$node_(2) set Z_ 0.000000000000$node_(2) set Y_ 199.373306816804$node_(2) set X_ 591.256560093833$node_(1) set Z_ 0.000000000000$node_(1) set Y_ 345.357731779204$node_(1) set X_ 257.046298323157$node_(0) set Z_ 0.000000000000$node_(0) set Y_ 239.438009831261$node_(0) set X_ 83.364418416244$god_ set-dist 0 1 1$ns_ at 50.000000000000 "$node_(2) setdest 369.463244915743

170.519203111152 3.371785899154"$ns_ at 51.000000000000 "$node_(1) setdest 221.826585497093

80.855495003839 14.909259208114"$ns_ at 33.000000000000 "$node_(0) setdest 89.663708107313

283.494644426442 19.153832288917"

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Scenario Generator: Traffic• Generating traffic pattern files

– CBR/TCP trafficns cbrgen.tcl [-type cbr|tcp] [-nn nodes] [-seed ns cbrgen.tcl [-type cbr|tcp] [-nn nodes] [-seed seed] [-mc connections] [-rate rate (pkt/s)]seed] [-mc connections] [-rate rate (pkt/s)]

– CBR trafficCBR trafficns cbrgen.tcl –type cbr –nn 20 –seed 1 –mc 8 ns cbrgen.tcl –type cbr –nn 20 –seed 1 –mc 8 -rate 4-rate 4– TCP trafficns cbrgen.tcl –type tcp -nn 15 -seed 0 –mc 6ns cbrgen.tcl –type tcp -nn 15 -seed 0 –mc 6Default packet size: 512 bytes, hardwired in script!Start time uniform in [0, 180] s, hardwired in script!

• To evaluate routing, which traffic type would you use?

• Source: ns-2/indep-utils/cmu-scen-gen/ns-2/indep-utils/cmu-scen-gen/

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A Traffic Scenario

set udp_(0) [new Agent/UDP]$ns_ attach-agent $node_(0) $udp_(0)set null_(0) [new Agent/Null]$ns_ attach-agent $node_(2) $null_(0)set cbr_(0) [new Application/Traffic/CBR]$cbr_(0) set packetSize_ 512$cbr_(0) set interval_ 4.0$cbr_(0) set random_ 1$cbr_(0) set maxpkts_ 10000$cbr_(0) attach-agent $udp_(0)$ns_ connect $udp_(0) $null_(0)$ns_ at 127.93667922166023 "$cbr_(0) start"…….

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# Define node movement model source <movement-scenario-files>

# Define traffic modelsource <traffic-scenario-files>

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# Tell ns the simulation stop time $ns at 200.0 “$ns halt”

# Start your simulation $ns run

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Energy Extension

• Makes MobileNode energy-aware• Enable by adding options:$ns_ node-config \

–energyModel EnergyModel

-initialEnergy100.0

-txPower 0.6

-rxPower 0.2

21

Outline



22

Wireless Internals

• MobileNode– Basic entity with address and port de-

muxes, routing agent, &c.– Stack of network components, including

IFQ, LL, MAC, NetIF, radio propagation model, &c.

• Wireless channel

23

Portrait of A Mobile Node

Node

ARP

Propagation and antenna models MobileNode

LL

MAC

PHY

LL

CHANNEL

LL

MAC

PHY

Classifier: Forwarding

Agent: Protocol EntityNode Entry

LL: Link layer object

IFQ: Interface queue

MAC: Mac object

PHY: Net interface

protocolagent

routingagent

addrclassifier

portclassifier

255

IFQIFQ

defaulttarget_

Radio propagation/antenna models

Prop/ant

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Mobile Node : Components

• Classifiers• defaulttarget_ points to routing agent

object• 255 is the port id assigned for rtagent_

• Routing agent• Ad hoc routing protocol, e.g., AODV,

DSDV, DSR; or directed diffusion

25

Mobile Node: Components

• Link Layer– Same as LAN, but with a separate ARP module– Looks up IP-to-MAC mappings using ARP

• ARP– Resolves IP address to hardware (MAC) address– Broadcasts ARP query

• Interface queue (IFQ)– Gives priority to routing protocol packets– Has packet filtering (search and remove)

capacity

26


• MAC– 802.11

• IEEE RTS/CTS/DATA/ACK for unicast• Sends DATA directly for broadcast

• Network interface (PHY)– Used by MobileNode to access channel– Stamps outgoing packets with meta-

data– Interface with radio/antenna models

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• Radio Propagation Model– Friss-space model: attenuation at near

distance– Two-ray ground reflection model:

attenuation at far distance– Shadowing model: probabilistic

• Antenna– Omni-directional, unity-gain

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Wireless Channel

• Duplicate packets to all mobile nodes attached to the channel except the sender

• It is the receiver’s responsibility to decide if it will accept the packet– Collision is handled at individual

receiver– O(N2) computation!

29

Wireless Trace Support• CMU trace format differs from standard ns trace

format!• Configurable tracing:

– MAC (very voluminous!)– Router forwarding– Agent events– Movement events

• Format described in detail in ns manual• When in doubt, no substitute for reading the code!• Shortest path lengths logged per pkt rx (cost in-

core?)

• “New” wireless trace format– appears not to be in wide use yet– same information, formatted differently

30

Outline



31

Simulation as Way to Enable Area

• Ad hoc routing: huge system deployment/debugging cost

• 1998 Broch et al. paper a watershed for ad hoc routing: first even comparison of wide field of protocols

• CMU ns wireless “extensions” the basis of most ad hoc networking research for next 5+ years

32

Simulation as Way to Kill Area

• Simulators don’t evaluate motivation!– Why are 500 laptops in a gymnasium not

simply connecting to base stations?• The founding of MobiHoc

– cf. the founding of SIGMETRICS…• The founding of MobiSys• Secret tip: building a real system

dramatically increases chances of acceptance! (because it’s HARD)

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Things to Investigate Using ns

• Coarse notion of capacity• Coarse notion of effect of mobility• Fine-grained behavior of your routing

(or other hop-by-hop) protocol– Only place you can easily have

“centralized’ view!

34

Things Not to Investigate Using ns

• Realistic loss behavior (interference, multi-path fading, …)

Bro

ad

cast

Packet

Delivery

Pro

bab

ilit

y

Node Pair

Roofnet measurements [SIGCOMM 2004]

35

Not in ns (cont’d)

• Realistic topology information– Roofnet finding: RTS/CTS useless in

outdoor network!– Hidden terminal problem still mainstay of

undergraduate networking courses everywhere…

– GPSR free space ns simulation debacle (more later)

• Fine-grained mobility behavior– Random Waypoint corresponds little to

reality– GPSR density anomaly (more later)

36

When to Roll Your Own Simulator

• GPSR greedy-only simulator– properties of node density, not of fine-

grained radio propagation– ~250 lines of C, a morning’s work– far faster than ns will ever be

• Simple visualization– GPSR topology visualizer

• find connected components• show planar subgraphs• animate forwarding

37

Outline



38

Central idea: Machines can know their geographic locations.

Route using geography. [MobiCom 2000]

• Packet destination field: location of destination• Nodes all know own positions, e.g.,

– by GPS (outdoors)– by surveyed position (for non-mobile nodes)– by short-range localization (indoors, [AT&T Camb, 1997],

[Priyantha et al., 2000])– &c.

• Two forwarding algorithms:– Greedy mode simply chooses closest neighbor to destination– Perimeter mode recovers when no closer next hop available,

by routing on planar subgraph of full network graph

Scalability: tiny state per router; low routing protocol overhead; approximates shortest paths; high delivery success rate

Greedy Perimeter Stateless Routing (GPSR)

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Greedy Forwarding

• Nodes learn immediate neighbors’ positions from beaconing/piggybacking on data packets

• Locally optimal, greedy next hop choice:– Neighbor geographically nearest destination

Dx

y

40

Greedy Forwarding Failure

Greedy forwarding not always possible! Consider:D

x

zv

void

w y

How can we circumnavigate voids?…based only on one-hop

neighborhood?

41

Well-known graph traversal: right-hand ruleRequires only neighbors’ positions

Void Traversal: The Right-hand Rule

x

y zDoesn’t work when edges in graph cross one another!

42

Planarized Graphs: Example

200 nodes, placed uniformly at random on 2000-by-2000-meter region; 250-meter radio range

Full Graph GG Subgraph RNG Subgraph

43

Packet Delivery Success Rate(50, 200; Dense)

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GPSR: Making it Real

• We implemented full GPSR for Berkeley mote sensors [NSDI 2005]– 3750 lines of nesC code– also includes: simple link thresholding, ARQ

• Deployed on Mica 2 “dot” mote testbeds– 23-node, 50-node subsets of 100-node

network in office building (Soda Hall; office walls; 433 MHz)

– 40-node network in office building (Intel Research Berkeley; cubicles; 900 MHz)

• Delivery success workload: 50 packets between all node pairs, serially

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50-Node Testbed, Soda Hall

GAME OVEROnly 68.2% of node pairs connected!!

What’s going on here?!

46

Planar, but Partitioned

Output of GPSR’s Distributed GG

(arrows denote unidirectional links)

Absorption, reflection (multi-path), interference, antenna orientation differences, &c., lead to non-uniform radio ranges.RNG and GG partition graphs when radio ranges not uniform!Solution: entirely new protocol, CLDP, for removing crossing edges [NSDI 2005]. Provably correct on all connected graphs.

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Key Lessons and Conclusion

• Understand your algorithm’s correctness assumptions

• Does the simulator model these properties accurately, or at least pessimistically?

• Fading, interference, loss rate particular pitfalls

• No substitute for building—even moreso than for Internet congestion control, as propagation too complex to model accurately

48

UCL: A Tradition of Great Networking Research in London

• Hiring junior and senior networking faculty

• Application deadline:5th January, 2006

• Details at http://www.cs.ucl.ac.uk/

• Why UCL?– Research: sdr, rat,

Landmark Routing, NAT, XORP, TFRC, XCP, GPSR, CLDP, GHT, Autograph, Polygraph, …

– Students (Paul Francis, Mark Handley, Jon Crowcroft, …)

– LONDON

http://www.cs.ucl.ac.uk/

how (not) to simulate wireless networks with ns brad karp [email protected] university college...

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