Dynamically configure roles

(e.g., DNS Stub Name Server or SIP Proxy)

Dynamically configure links (e.g., IP address of best root, forwarding or master NSs)

Task 1.2 Autonomous Internetworking

Prepared through collaborative participation in the Communications & Networks Consortium sponsored by the U. S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD-DAAD-19-01-2-0011. The U. S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon.

The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U. S. Government.

FY05 Plans

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

1000000

0 10 20 30 40 50 60 70 80 90 100

Number of nodes (n)

Rou

ting

Ove

rhea

d (b

its)

One Domain

SQRT(n) Domains (based only on topology)

SQRT(n) Domains (based on topology and mobility)

Task 1.2.1 New protocols to maintain reachability in large dynamic ad hoc networks Challenges: Existing solutions poorly handle loss of root/home servers,

brittle linkages (e.g., net splits), multi-homing, and HAIPE.

Proposals: Integrated location architecture (DNS SIP, Presence, IM) with

autoconfigured, Efficient and Robust Inter-domain linkages.

Challenges: Balancing fast, simple distributed mechanisms with

more optimal global mechanisms. Quantifying the theoretical advantages of dividing a

network into independent routing domains.

Proposals: Simultaneously optimizing large networks across multiple network functions, layers, and levels of hierarchy. Faster Simulated Annealing and other techniques to optimize more complex cost functions over more nodes. Better local maintenance algorithms based on the reclustering cost functions. Optimize for specific routing metrics (e.g., maximum path length and percentage suboptimatily) .

Task 1.2.2 Automatic domain generation for routing and other functions, using complex multi-function, cross-layer, and multi-level optimization

Domain 3.X

Domain 7.X

Domain 5.X

Domain 7.X

Domain 3.X

Domain 5.X Domain 4.X

v@Z

e@X

v@Z

e@X

f@M

c@L

Domain 1.X

d@L Domain 1.X

d@L

f@MN1

N2

N4

N3

N4

N3N1

Dynamic “black” wireless network

Manage IP address configuration

11

10

9

126

7

8

5

1

3 4

2

CID = 9 CID = 5

CID = 1

11

10

9

126

7

8

5

1

3 4

2

CID = 9 CID = 5

CID = 1

Pac

ket

loss

due

to

MA

C c

ollis

ions

Minimize Routing Path Length Suboptimality

100 nodes, 4 Clusters

0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12 13

Flat Shortest Path (Dijkstra)

Avg

. Ro

ute

Pat

h L

eng

th (

ho

ps)

FlatShortestPath GivenCHsPreOpt GivenCHsPostOpt CombinedOpt

2 2

1( ) min , ...., KJ C Var C C

Minimize Routing Path Length Suboptimality100 nodes, 4 Clusters

0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12 13

Flat Shortest Path (Dijkstra)

Avg

. Ro

ute

Pat

h L

eng

th (

ho

ps)

FlatShortestPath GivenCHsPreOpt GivenCHsPostOpt CombinedOpt

2 2

1( ) min , ...., KJ C Var C C

HAIPE

HAIPE

HAIPEHAIPE

HAIPE

N2

HAIPEHAIPE

HAIPE

HAIPE

a) Hierarchy Benefits b) Hierarchy Drawbacks

c) Local Maintenance

Task 1.2.3 Highly Adaptive Component Based Routing Protocols that are able to change all functional aspects in response to changes in environment and network demands

87.69

7.691.54 0 1.54 1.54

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7

Number of RTT

Per

cen

tag

e

Dr. Anthony McAuley, Telcordia, mcauley@research.telcordia.comDr. Stephan Bohacek, University of Delaware, bohacek@udel.edu

Routing protocols constructed from different components

Classes of components

The selection of components depends on the demands placed on the network and the operating environment.

on demandflooding

proactive topology discoverycluster-based

topology discovery

local repairfloodingtopology

informationflood to

source tree

route repair

first foundleasthops

route selection

leastpower

longest life

low mobility low powerlow traffic

delay tolerant

high mobility delay intolerantlarge topology

authenticationgame-

theoretic

security

Components of routing protocols

Task I. Taxonomy of components•Find the elementary components of routing protocols•Functional description of elementary components•Component interaction and dependency graph

Task 2. Performance analysis of componentsIdentification of performance bottlenecksPerformance of routing components

Topology information disseminationMulticastBroadcastTopology discovery

Protocol performanceSecurityScalability

A complete revision of MANET routing protocols.Eight research groups jointly developing a single protocol. Systematic analysis and development of MANET protocols.Deep insight into the routing protocols.

Routing table

Interest table

Route in Packets

Binary Tree

Cost Table

Geographic Information

Exact Route

Route Guidence

Route Representation/Formation

Route Discovery Proactive Reactive

Route Maintenance---Failure Handling

Network wideupdate

Limit update

Route rediscovery

Local repair

Route cache

Alternative route

Dr. Ken Young, Telcordia, kcy@research.telcordia.comMr. Hal Harrelson, ARL, hharrelson@arl.army.mil

a) Optimized domain creation using Simulated Annealing with complex cost functions and constraints

b) Domain maintenance reassociation using the same cost functions used in domain generation

Prepared through collaborative participation in the Communications & Networks Consortium sponsored by the U. S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD-DAAD-19-01-2-0011. The U. S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon.

The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U. S. Government.

FY04 Accomplishments

Number of Sessions

Unitary Plane

Srp = 1

Srp = 100

Srp = 10

K=10, l=5, m=med, d=20

Mobility Rate

Indirect, through HA

Direct to CN

lPDCSlBUDSkREG

mkPDCSkREGd

cn

d

cn

d

dh

d

tri

d

ih

prrm

prm)()()(

)()(

;

MIP

MIP

6

4

Cp Cost to process packet/message at a node.Ct Cost to transmit one message over one hopm, mobility rate p, packet arrival rate per sessionSr , number of sessionsw Number of LA registrations for each HA registrationd Number of moves results are averaged over

Mobile Node

d = 0

d = 20

Unitary Plane

p= m=Sr=1

Task 1.2.1 A new analytical framework for performance evaluation of mobility protocols

lkmlk

Degradation of the Clustering Map CostApproach 1 (A1-Lower ID) vs. Approach 2 (A2-Similar Mobility)

0.0E+00

2.0E+09

4.0E+09

6.0E+09

8.0E+09

1.0E+10

1.2E+10

1.4E+10

Time (secs)

Co

st o

f C

lust

erin

g M

ap

Lower ID (A1) Similar Mobility (A2)

Objective Cost Function

Balanced Size Clusters (1)(2)

Balanced Diameter Clusters (3)(4)

Balanced Clusters with minimum Border Routers.

(5)

Cluster members move in a similar direction, so we expect longer durations of stable cluster membership

(6)(7)

Cluster members have similar velocity, so expect more stable cluster membership

(8)

Links among cluster members have long expiration time estimates. Improves the lifetime of the generated hierarchy

(9)

Cluster members move with similar direction and velocity. Like (6),(7),(8) capturing more node dynamics (e.g., direction and velocity)

(10)

2 2

1( ) min , ...., KJ C Var C C

2

1

( ) minK

ii

J C C

2

1

( ) mini

K

Ci

J C d

1 2

2 2 2min , ,....,KC C CJ C Var d d d

2 2

11

min ,....,i

K

K Ci

J C Var C C BR

,

2

1 , 1

( ) minz

i j

CK

rz i j

J C

1,2 1,

1

min ,...,z zC Cz z

K

r rz

J C Var

,

2

2

1 , 1

minz

zi j

CK

rz i j

J C U

2

1 , 1

minzCK

z ijz i j

J C I LET

,

,

2

, 1

1

, 1

2*maxmin

180

z zi j

zi j

Cr

Ki j

Cz r

i j

U

SJ C

n

Border Router for MN

Subnet

Networkm k

p

HAMN

MN

HACN

l

Local Mobility Agent for MN

LAMN

q

Home Agent for MN

BRMN

LACNSubnet

CNBRCN

Task 1.2.2 Improved automatic domain generation providing scalability, manageability and efficiency in large heterogeneous networks, such as FCS and WIN-T

c) Domain maintenance beacon quickly detects constraint violations

T=0

Merge

Split

T=1

T=2

T=3

T=4

Domain ID = 6

Domain ID = 9

2 domains

Domains Merge

Low Priority1 domain

Domain split

Self elected beacon node (new domain ID = 3)b

2 domains

High Priority

Detects

Detects

MIP6 better

MIP4 better

Task 1.2.3 Routing

Task 1.2 Autonomous Internetworking

MIP6

MIP4MIP6

MIP4

Dr. Anthony McAuley, Telcordia, mcauley@research.telcordia.comDr. Stephan Bohacek, University of Delaware, bohacek@udel.edu

Dr. Ken Young, Telcordia, kcy@research.telcordia.comMr. Hal Harrelson, ARL, hharrelson@arl.army.mil

• Key observation– Idling consumes significant amount of energy– Unattended ground sensors (UGS): hard energy constraint

• To conserve energy: turn off the sensors – duty cycling• Different types of duty cycling: Single radio and Dual radio• Goal: reducing duty cycle while maintaining coverage

Network Coverage with Low Duty Cycled SensorsNetwork Coverage with Low Duty Cycled Sensors

Objective• Analyze the applicability of recent

research in authentication techniques for secure routing

Results• Traditional signature and new

signature techniques outperform Zhang’s authentication schemes

• In our hop-by-hop authentication scenarios Zhang’s schemes are preferred at rates above 2 Mbps and communication energy costs below 4 mJ/kbps

P-III M (Ultra Low) (N = 10 Hops End-to-End Authentication)

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1 10 100 1,000 10,000

Effective Data Rate (Kbps)

Del

ay (

bit

s)

DSA

ECDSA F_2

ECDSA_F_P

BLS F_3^97

Z98 S4 SHA

Z98 S4 MD5

Z98 S5 SHA

Z98 S5 MD5

C&C F_3^97

P-III M (Ultra Low) (N = 10 Hops End-to-End Authentication)

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

1.0E+09

1.0E+10

0.01 0.10 1.00 10.00 100.00 1,000.00 10,000.00

Energy per Unit Comms (mJ/kb)

En

erg

y (m

J)

DSA

ECDSA F_2

ECDSA_F_P

BLS F_3 9̂7

Z98 S4 SHA

Z98 S4 MD5

Z98 S5 SHA

Z98 S5 MD5

C&C F_3^97

Evaluating the Trade-offs between Broadcasting and MulticastingEvaluating the Trade-offs between Broadcasting and MulticastingMain resultsThere is no clear winner between broadcasting and multicasting.The scenario in question dictates the choice.

For large group sizes with a single multicast source, SBA (or broadcast) is preferable. For small group sizes with single source, ODMRP (or multicast) is a clear choice

In high node mobility, SBA (or broadcast) is preferableWith single source, ODMRP (or multicast) is preferable in dense networks

Cost of Security forCost of Security for Tactical MANETSTactical MANETS – Modular architecture facilitates

customized configurations – OS abstraction for rapid development

and testing– Smooth transition of shared code

from simulation testbed to prototypes

OPNETOPNET

Off-line Analysis

Logging

PackbotPackbot

Radio

MAC

Transceiver Duty Cycling

Transmit Power Control

NeighborDiscovery

Routing

Shared Network Layer

Protocols

IP

Applications

Multi-hop Routing Protocol Integration with PackbotsMulti-hop Routing Protocol Integration with Packbots

Real-Time Network Monitoring and Management