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Task 1.2 Autonomous Internetworking
Dr. Anthony McAuley, Telcordia, [email protected]
Dr. Stephan Bohacek, University of Delaware, [email protected]
Dr. Ken Young, Telcordia, [email protected]
Mr. Hal Harrelson, ARL, [email protected]
FY05 Plans
 Task 1.2.1 New protocols to maintain reachability in large dynamic ad hoc networks
Challenges:
N1
 Existing solutions poorly handle loss of root/home servers,
brittle linkages (e.g., net splits), multi-homing, and HAIPE.
v@Z
N3
f@M
d@L
Domain 7.X
Domain 3.X
HAIPE
Dynamic “black”
wireless network
 Integrated location architecture (DNS SIP, Presence, IM) with
autoconfigured, Efficient and Robust Inter-domain linkages.
HAIPE
N2
Domain 5.X
Domain 1.X
Domain 7.X
HAIPE
Dynamically configure links
(e.g., IP address of best root,
N2
forwarding or master NSs)
e@X
d@L
N3
HAIPE
Domain 3.X
N4
HAIPE
v@Z
f@M
Manage IP address
configuration
Domain 1.X
HAIPE
Proposals:
Dynamically configure roles
(e.g., DNS Stub Name
Server or SIP Proxy)
N1
HAIPE
N4
HAIPE
HAIPE
c@L
e@X
Domain 5.X
Domain 4.X
 Task 1.2.2 Automatic domain generation for routing and other functions, using complex
multi-function, cross-layer, and multi-level optimization

 
Challenges:
Minimize Routing Path Length Suboptimality
100 nodes, 4 Clusters
J (C )  min Var C1 ,...., CK
2
2
18
800000
SQRT(n) Domains (based only on topology)
700000
SQRT(n) Domains (based on topology and mobility)
600000
500000
400000
300000
200000
100000
0
0
10
20
30
40
60
70
80
90
100
Number of nodes (n)
Proposals:




50
Avg. Route Path Length (hops)
 Balancing fast, simple distributed mechanisms
with more optimal global mechanisms.
 Quantifying the theoretical advantages of dividing
a network into independent routing domains.
900000
One Domain
Packet loss due to MAC collisions
Routing Overhead (bits)
1000000
16
14
12
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Flat Shortest Path (Dijkstra)
FlatShortestPath
a) Hierarchy Benefits
GivenCHsPreOpt
GivenCHsPostOpt
CombinedOpt
b) Hierarchy Drawbacks
CID = 9
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) .
CID = 5
7
10
12
6
8
9
11
5
1
3
2
4
CID = 1
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
Classes of components
topology
discovery
route
repair
route
selection
Components of
routing protocols
on demand
flooding
proactive
topology
discovery
clusterbased
local repair
flooding
topology
information
flood to
source tree
first found
least
hops
least
power
longest life
low mobility
low power
low traffic
delay tolerant
Routing protocols
constructed from
different components
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.
security
authentication
gametheoretic
The selection of components
depends on the demands
placed on the network and the
operating environment.
high mobility
delay intolerant
large topology
Task 2. Performance analysis of components
Identification of performance bottlenecks
Performance of routing components
Topology information dissemination
Multicast
Broadcast
Topology discovery
Protocol performance
Security
Scalability
Task I. Taxonomy of components
•Find the elementary components of routing protocols
•Functional description of elementary components
•Component interaction and dependency graph
Exact
Route
Route
Representation/
Formation
Route
Guidence
100
90
Interest Route in Binary
table
Packets Tree
Route
Discovery
Cost
Table
Geographic
Information
70
60
50
40
30
Reactive
Proactive
80
Percentage
Routing
table
87.69
20
7.69
10
1.54
0
1.54
3
4
5
1.54
0
Route
Maintenance
---Failure
Handling
1
Network wide
update
Limit
update
Route
rediscovery
Local
repair
Route
cache
Alternative
route
2
6
7
Number of RTT
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.
Task 1.2 Autonomous Internetworking
Dr. Anthony McAuley, Telcordia, [email protected]
Dr. Stephan Bohacek, University of Delaware, [email protected]
Dr. Ken Young, Telcordia, [email protected]
Mr. Hal Harrelson, ARL, [email protected]
FY04 Accomplishments
 Task 1.2.1 A new analytical framework for performance evaluation of mobility protocols
p= m=Sr=1
d=0
MIP6
MIP4
n
K=10, l=5, m=med, d=20
MN
HACN
MIP6
MIP4
MIP6
better
k
m
d = 20
Border Router
for MN
Network
LACN
l
Mobile
Node
p
Subnet
MN
Cp Cost to process packet/message at a node.
Ct Cost to transmit one message over one hop
m, mobility rate
p, packet arrival rate per session
Sr , number of sessions
w Number of LA registrations for each HA registration
d Number of moves results are averaged over
Srp = 1
Srp = 10
m REG ih k   S r  p PDC tri k ; m 
MIP4

(d )
(d )
(d )
MIP6 m REG dh k   S r BUD cn l   S r  p PDC cn l 
(d )
(d )

Srp = 100
Number of Sessions
q
BRMN
Subnet
MIP4
better
Local Mobility Agent
for MN
LAMN
BRCN
CN
Indirect, through HA 
k l  m  k l
Direct to CN

Home Agent
for MN
HA
Mobility Rate

 Task 1.2.2 Improved automatic domain generation providing scalability, manageability and
efficiency in large heterogeneous networks, such as FCS and WIN-T
2 domains
Degradation of the Clustering Map Cost
Approach 1 (A1-Lower ID) vs. Approach 2 (A2-Similar Mobility)
Cost Function
K
J (C )  min  Ci



(3)
(4)

Balanced Clusters with minimum Border
Routers.

K
  (5)
2
2
J  C   min Var C1 ,...., CK    BRCi  
 i 1


Cluster members move in a similar
direction, so we expect longer durations
of stable cluster membership
2
 K  Cz
 
J (C )  min      ri , j  
 z 1  i , j 1
 

K

J  C   min Var  r z ,..., r z

1,2
Cz 1, Cz
 z 1

Cluster members have similar velocity, so
expect more stable cluster membership
Links among cluster members have long
expiration time estimates. Improves the
lifetime of the generated hierarchy
Cluster members move with similar
direction and velocity. Like (6),(7),(8)
capturing more node dynamics (e.g.,
direction and velocity)
1.2E+10


(6)
(7)
2
 K  Cz
  (8)
2
J  C   min     U r z  
 z 1 i , j 1 i , j  


2
 K  Cz
 (9)
J  C   min     I z  LETij   
 z 1  i , j 1
 

T=1
Merge
1.0E+10
1 domain
Low Priority
High Priority
8.0E+09
6.0E+09
T=2
4.0E+09
Domain split
2.0E+09
0.0E+00
T=3
2
  Cz
Urz
 
i
,
j
 
  (10)
 K i
, j 1 2*max  S   
J  C   min   
 
 z 1  Cz  ri , j
 
    180
 
i
,
j

1
 

11
8
14
1
16
5
18
8
21
2
23
5
25
9
28
2
30
6
32
9
35
3
37
6
40
0
42
3
44
7
47
0
49
4
i 1
J  C   min Var  dC21 , dC22 ,...., dC2K 
2
94
 
J (C )  min  dC2i

Detects
Detects
71
K
2
(1)
(2)
24
47
 
J (C )  min Var C1 ,...., CK
Balanced Diameter Clusters
Domains Merge
2
i 1
0
Balanced Size Clusters
T=0
1.4E+10
Cost of Clustering Map
Objective
Domain ID = 6
Domain ID = 9
Split
2 domains
Self elected beacon
node (new domain ID
= 3)b
Time (secs)
Lower ID (A1)
a) Optimized domain creation using Simulated Annealing
with complex cost functions and constraints
 Task 1.2.3 Routing
Similar Mobility (A2)
b) Domain maintenance reassociation using the
same cost functions used in domain generation
T=4
c) Domain maintenance beacon
quickly detects constraint violations
Evaluating the Trade-offs between Broadcasting and Multicasting
Network Coverage with Low Duty Cycled Sensors
• 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
Main results
There is no clear winner between broadcasting and multicasting.
The scenario in question dictates the choice.
For
large group sizes with a single multicast In high node mobility, SBA (or broadcast)
source, SBA (or broadcast) is preferable.
is preferable
For small group sizes with single source,
With single source, ODMRP (or
ODMRP (or multicast) is a clear choice
multicast) is preferable in dense networks
Cost of Security for
Tactical MANETS
Multi-hop Routing Protocol Integration with Packbots
P-III M (Ultra Low) (N = 10 Hops End-to-End Authentication)
1.0E+06
DSA
ECDSA F_2
ECDSA_F_P
BLS F_3^97
Z98 S4 SHA
Z98 S4 MD5
1.0E+04
Z98 S5 SHA
Z98 S5 MD5
C&C F_3^97
1.0E+03
1.0E+02
1
10
100
1,000
10,000
Effective Data Rate (Kbps)
Real-Time Network Monitoring and
Management
Packbot
P-III M (Ultra Low) (N = 10 Hops End-to-End Authentication)
Applications
IP
1.0E+10
1.0E+09
DSA
1.0E+08
ECDSA F_2
Energy (mJ)
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
Delay (bits)
1.0E+05
– Modular architecture facilitates
customized configurations
– OS abstraction for rapid development
and testing
– Smooth transition of shared code
from simulation testbed to prototypes
ECDSA_F_P
1.0E+07
Shared
Network Layer
Protocols
BLS F_3^97
Z98 S4 SHA
1.0E+06
Logging
Routing
Z98 S4 MD5
Z98 S5 SHA
1.0E+05
Z98 S5 MD5
C&C F_3^97
1.0E+04
Transmit Power
Control
1.0E+03
1.0E+02
0.01
Neighbor
Discovery
0.10
1.00
10.00
100.00
Energy per Unit Comms (mJ/kb)
1,000.00
10,000.00
Transceiver
Duty Cycling
MAC
Radio
Off-line
Analysis
OPNET
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.