Multicast ad hoc Multicast ad hoc networksnetworks

Multicast in ad hoc netsMulticast in ad hoc nets Review of Multicasting in wired networksReview of Multicasting in wired networks Tree based wireless multicastTree based wireless multicast Mesh based wireless multicast – ODMRPMesh based wireless multicast – ODMRP Performance comparisonPerformance comparison

Scalable multicastScalable multicast M-LANMARM-LANMAR Backbone Backbone

Reliable, congestion controlled multicastReliable, congestion controlled multicast RALM, RALM with M-LANMARRALM, RALM with M-LANMAR

LANMARLANMAR Key insight: Key insight: nodes move in teams/swarmsnodes move in teams/swarms Each team is mapped into aEach team is mapped into a logical subnet logical subnet IP-like Node addressIP-like Node address = <subnet, host> = <subnet, host> Address compatible with IPv6Address compatible with IPv6 Team leaderTeam leader (Landmark) (Landmark) elected in each group elected in each group

Logical SubnetLogical Subnet

LandmarkLandmark

Scalable Ad hoc multicastingScalable Ad hoc multicasting

Multicast (ie, transmit same message to all Multicast (ie, transmit same message to all member of a group) critical in battlefieldmember of a group) critical in battlefield

““Multiple unicast” does not scaleMultiple unicast” does not scale Current ad hoc multicast solutions:Current ad hoc multicast solutions:

inappropriateinappropriate They do not exploit affinity team modelThey do not exploit affinity team model multicast tree approach is “fragile” to multicast tree approach is “fragile” to

mobility;mobility; no congestion control; no reliable end to end no congestion control; no reliable end to end

deliverydelivery Proposed approach:Proposed approach:

TEAM MulticastTEAM Multicast

swarmswarm

Command postCommand post

Swarm Swarm LeaderLeader

UAVs: - equipped with video, chemical sensors - read data from ground sensors - “fuse” sensor data inputs - multicast fused data to other teams

Team Multicasting

Multicast exampleMulticast example

Attack!

Attack!

Attack!

Attack!

Attack!

Command Post

All TaskForce Nodes

Two-tier team multicast: Two-tier team multicast: Multicast-Enabled Landmark Multicast-Enabled Landmark

(M-LANMAR) (M-LANMAR) Extension of LANMAR enabling Extension of LANMAR enabling

multicastmulticast Inter-teamInter-team communication: communication: unicastunicast

tunneling tunneling from the source to the from the source to the representative of each subscribed representative of each subscribed team team

Intra-teamIntra-team communication: scoped communication: scoped floodingflooding within a team within a team

Source node

LM2

LM3

Subscribed Teams

LM4

Tunneling to landmarksFlooding

Flooding

Scope = 2

Scope = 2

M-LANMAR

Advantages of M-LANMARAdvantages of M-LANMAR

Reduced control traffic Reduced control traffic overheadoverhead Scalable to Scalable to thousandsthousands of nodes of nodes Enhanced Enhanced Congestion controlCongestion control and and

ReliabilityReliability (because of (because of TCPTCP control on control on unicast tunnels)unicast tunnels)

M-LANMAR multicastM-LANMAR multicast

ScalabilityScalability

Objective: test M-LANMAR scalabilityObjective: test M-LANMAR scalability Compared withCompared with

ODMRPODMRP Flooding Flooding

Simulation EnvironmentSimulation Environment QualNetQualNet 1000 nodes 1000 nodes forming forming 36 teams36 teams on on 6000 x 6000 m6000 x 6000 m22 field field CBR traffic (CBR traffic (512 bytes512 bytes/packet, 1packet/sec)/packet, 1packet/sec)

Simulation ResultsSimulation Results

As the number of multicast groups increasesAs the number of multicast groups increases M-LANMAR achieves M-LANMAR achieves high delivery ratiohigh delivery ratio (by (by

unicast tunneling and flooding)unicast tunneling and flooding) ODMRP suffers from large control overhead ODMRP suffers from large control overhead

and collisionsand collisions

Multiple Unicast v.s. Mesh Multiple Unicast v.s. Mesh StructureStructure

Builds a mesh Builds a mesh between landmarksbetween landmarks Load BalancingLoad Balancing Better ReliabilityBetter Reliability

source

landmark

00.10.20.30.40.50.60.70.80.9

2 m/s 10 m/s 15 m/s 20 m/s

Mobility (meter/sec)

Deliv

ery

Ratio

Team Multicast-Multiple Uni Team Mutlicast-MESH

Enhanced Scalability Enhanced Scalability with with a Mobile Backbonea Mobile Backbone

• Multicast across Large systems of swarms does not scale well• excessive

protocol overhead

• Long paths break

• Swarms separate

• Enter Mobile Backbone!

src

dst

Simulation studySimulation study - swarm motion - swarm motion

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50

Mobility (Group movement Speed)

Pack

et D

elive

ry Ra

io

ODMRP w/ BB Flat ODMRP

Implemented in QualNet 3.6Implemented in QualNet 3.6 Total 300 nodes over a 5000 Total 300 nodes over a 5000

x 5000 field: x 5000 field: 20 candidate backbone nodes20 candidate backbone nodes 14 swarms, 20 ground nodes 14 swarms, 20 ground nodes

in each swarmin each swarm Traffic generated from Traffic generated from

single source to single source to 30 receivers 30 receivers across different groupsacross different groups

BandwidthBandwidth Allocation - Allocation - backbone/ground: 1Mbps backbone/ground: 1Mbps flat network: 2Mbpsflat network: 2Mbps

Mobile backbone sMobile backbone significantignificantlyly improve improves s delivery in swarm/group motiondelivery in swarm/group motion

Simulation studySimulation study - random - random roamingroaming

Backbone network Backbone network improvements for random improvements for random motion even higher than with swarmsmotion even higher than with swarms

Random distribution of Random distribution of 500 nodes 500 nodes oon n a a 550000x50000x50000 fieldfield

Nodes move randomlyNodes move randomly Ground network is dense Ground network is dense

and connectedand connected Single multicast group: Single multicast group:

one source, one source, 30 receivers30 receivers BandwidthBandwidth Allocation - Allocation -

backbone/ground:1Mbsbackbone/ground:1Mbs flat network: 2Mbpsflat network: 2Mbps

0

0.2

0.4

0.6

0.8

1

1.2

5 10 20 30 40

Mobility (node speed)

Pack

et D

eliv

ery

Ratio

ODMRP w/ BB flat ODMRP

Conclusions and Future WorkConclusions and Future Work M-LANMAR is a M-LANMAR is a scalablescalable multicast protocol multicast protocol

designed for large ad-hoc networks with designed for large ad-hoc networks with affinity affinity teamteam model model

Backbone Enhanced multicast:Backbone Enhanced multicast: Backbone + ODMRPBackbone + ODMRP achieves better achieves better

scalability than flat ODMRP (delivery ratio scalability than flat ODMRP (delivery ratio increases up to 50%)increases up to 50%)

Related workRelated work Coexistence of LANMAR and BackboneCoexistence of LANMAR and Backbone Impact of mobility (random, team, etc)Impact of mobility (random, team, etc) Mobility and traffic correlationMobility and traffic correlation Delay tolerant appls; “data ferrying”Delay tolerant appls; “data ferrying”