Architecture & Protocols
for Supporting Routing &
QoS in MANET
Navid NIKAEIN
http://www.eurecom.fr/~nikaeinn
© Navid Nikaein 2003
Outline







Introduction: Issues and Trade-Offs
Related Work
Architecture
Topology Management
Route Determination
Quality of Service Support
Conclusion and Open Issues
Issues in MANET
Mobile ad hoc networks:





Wireless  low-capacity  Collision
Mobility  time-varying resources
Lack of infrastructure  fully-distributed
Small devices  Limited resources
Routing & QoS
Link failure
Multihop
Routing
Routing Issues
Dilemma at a node:
“Do I keep track of routes to all destinations, or instead
keep track of only those that are of immediate
interest?”
 Three strategies:



Proactive: keep track of all.
Reactive: only those of immediate interest.
Hybrid: partial proactive / partial reactive.
Trade-off between routing overhead and delay
QoS Routing Issues

State of communication path should be
considered in QoS routing:

Resource availability and its stability
Cause longer path than shortest path
Trade-off between shortest path and optimal path
Assumption

Fully symmetric environment


All nodes have identical capabilities
Capabilities:
Transmission range,
 Battery life, processing capacity, buffer capacity
 Each node periodically sends a Beacon


All nodes participate in protocol operation
and packet forwarding [Michardi, Molva,
Crowcroft]
Related Work
Ad Hoc Routing
Topology-based
Proactive
OLSR
TBRPF
DSDV
WRP
CGSR
FSH-HSR
LANMAR
Reactive
DSR
AODV
RDMAR
ABR
SSR
TORA
Position-based
Hybrid
ZHLS
ZRP
CBRP
DDR+
HARP
Proactive
DREAM
Reactive
LAR
Hybrid
Terminodes
GLS
ALM
Architecture
AN ARCHITECTURE THAT SEPARATES [1]:
 Route Determination
With respect to Application
requirements
 Topology Management
With respect to Quality of
Network
Application
QoS Classes
HARP
QoS:
Delay TPut BE
DDR
Network
Protocol stack
Network Quality
QoC:
Power, buffer
Stability
QoS extension
Outline

Topology Management [2,3]


Route Determination


DDR- Distributed Dynamic Routing Algorithm
HARP- Hybrid Ad hoc Routing Protocol
Quality of Service Routing

LQoS- Layered Quality of Service
Topology Management


Intuition
DDR- Distributed Dynamic Routing Algorithm






Forest Construction
Zone Partitioning
Zone Behaviors
Simulation Model
Performance Results
Summary
Intuition
Generate a set of preferred paths in the network
Network Topology
Criteria
TREE
ZONE
Forest
BEACON
TREE …. TREE
ZONE …. ZONE
BEACON
Time
Forest Construction
Each node select the best node in its neighborhood
according to the given unique criteria, e.g. degree
If identical nodes, select the one with the higher ID
Theorem: Connecting each node to its preferred
neighbor yields to a forest [2]
3
c
5
f
4
b
MPR-tree [Qayyum] used in OLSR [Jaquet]
2
a
1
h
d
4
g
3
e
3
Forest Reduces the number of forwarding nodes
Zone Partitioning
Tree
Zone
Maintained using periodical beaconing
c
b
a
h
d
g
w
k
x
f
s
v
z
u
t
i
DDR
d
b
a
y
n
z2
c
z1
g
w
k
f
x
h
v
z
y
s
e
Zones :
Improves delay performance
Contributes in protocol scalability
t
u
i
n
e
z3
Criteria for FC [4]:
Quality of Connectivity (QoC)

Power level p  battery lifetime

Buffer level b  available unallocated buffer


Stability level s 
t=t1-t2: period
s ( x) 
| Nt0  Nt1 |
| Nt0  Nt1 |
 QoC =   s +   b (+   p )
The set of forwarding nodes belongs to the nodes
with the high quality
Zone Behaviors
Whatever the network density is, the zone diameter is bounded to 8
The average ratio of tree-path to shortest path is no longer than 2
Low Complexity O(N)
Zone Diameter
Tree Path / Shortest Path
Protocol Model


To study the effect of the proposed topology
management on routing performance ?
Hybrid Ad Hoc Routing Protocol (HARP) [5]





Dual mode: node level and zone level
Intra-zone and inter-zone routing
Discover the shortest path
Establish forward and reverse path
Maintenance
Simulation Model [Johansson,
Perkins, Broach]

Traffic model:






CBR
512 byte/packet
4 packets/second
Source 10, 20, 30
Performance Metrics:



Packet delivery fraction
Avg. E2E delay
Routing overhead
Movement model:

Random way point [Yoon]

50 nodes
1500mx300m
0-20 m/s (or 1-20m/s)
900 simulated seconds
Pause time=0, 30, 60, 150, 300,
600, 900
10 scenarios for each pause
time





Packet Delivery Fraction
Simple routing has a slightly better PDF in low traffic load
Routing+TM outperforms simple routing up to 20% as the traffic
load increases
10 sources
20 sources
30 sources
Avg. E2E Delay
Routing +TM significantly improves the delay performance up to 200ms
as the network conditions become stressful
10 sources
20 sources
30 sources
Routing Overhead (pkt)
Simple Routing outperforms Routing+TM in low/medium traffic load
Most of the packets produced by Routing+TM are the beacons
Reaction to link failure : Beacon vs. PREQ
Forest does reduce the broadcasting overhead
NOTE: Beacon is local while PREQ is global
10 sources
20 sources
30 sources
Routing Overhead (bytes)
Simple Routing outperforms Routing+TM in low/medium traffic load
Forest does reduce the broadcasting overhead
10 sources
20 sources
30 sources
Packet Delivery Fraction
The effect of mobility rate and traffic load on PDF
The fluctuation
The congestion  Adaptive Routing
Fluctuation
10 sources
20 sources
Fluctuation
Congestion
30 sources
Avg. E2E Delay
The effect of mobility rate and traffic load on DELAY
Shortest path is not enough !
The load balancing
Note: QoC =   s +   b , where  =2 &  = 1
Shortest path is not enough
10 sources
20 sources
Load Balancing
30 sources
Summary
Overall
Low traffic
Performance load
Medium
traffic load
High traffic
load
Low Mobility Routing
Similar
Routing
+TM
Medium
Mobility
Routing
+TM
Routing
+TM
Routing
+TM
Routing
+TM
Routing
High Mobility Similar
Outline

Topology Management


Route Determination [5,6]


DDR- Distributed Dynamic Routing Algorithm
HARP- Hybrid Ad hoc Routing Protocol
Quality of Service Routing

LQoS- Layered Quality of Service
Route Determination [5,6]

HARP- Hybrid Ah Hoc Routing Protocol




Intra-zone and Inter-zone routing
Query localization technique [Aggelou, Tafazolli]
Performance Results [Osafune]
Summary
Routing
Intra-zone Routing
z2
c
d
b
a
z1
g
w
k
x
f
v
src zone
z
Zone abstraction
y
s
t
r
Inter-zone Routing
h
Z1
Z2
u
i
m
n
e
z3
Z4
Z3
dst zone
z4
Shortcut intra-zone routing
- Zone level routing
- Distance estimation
Simulation Model [Johansson,
Perkins, Broach]

Traffic model:






CBR
512 byte/packet
4 packets/second
Source 10, 20, 30
Performance Metrics:



Packet delivery fraction
Avg. E2E delay
Routing overhead
Movement model:

Random way point [Yoon]

50 nodes
1500mx300m
0-20 m/s (or 1-20m/s)
900 simulated seconds
Pause time=0, 30, 60, 150, 300,
600, 900
10 scenarios for each pause
time





Packet Delivery Fraction
The effect of mobility and traffic load is not uniform
Congestion stems from the lack of load balancing in the protocols
Fluctuation point is a function of network parameters
The effect of cashing and/or neighboring table in high mobility
Fluctuation
10 sources
20 sources
Congestion
30 sources
Avg. E2E Delay
The effect of traffic load and mobility on the delay performance is non-uniform
Caching (DSR), route request (AODV), and beaconing/PREQ (HARP+TM)
Load balancing
Load balancing
10 sources
20 sources
30 sources
Routing Overhead (pkt)
Reaction to mobility (main cause of link failure)
Caching (DSR), route request (AODV), beaconing and PREQ (HARP+TM)
Effect of beaconing on battery lifetime [Toh]
No handshaking is required for beaconing
10 sources
20 sources
30 sources
Routing Overhead (bytes)
Reaction to mobility (main cause of link failure)
Caching (DSR), route request (AODV), beaconing and PREQ (HARP+TM)
Effect of beaconing on battery lifetime [Toh]
No handshaking is required for beaconing
10 sources
20 sources
30 sources
Summary
Overall
Low traffic
Performance load
Medium
traffic load
High traffic
load
HARP
Low Mobility
+TM
HARP
+TM
HARP
+TM
Similar
HARP
+TM
Similar
HARP
+TM
Medium
Mobility
HARP
+TM
HARP
High Mobility
+TM
Outline

Topology Management


Route Determination


DDR- Distributed Dynamic Routing Algorithm
HARP- Hybrid Ad hoc Routing Protocol
Quality of Service Routing [7]

LQoS- Layered Quality of Service
Quality of Service Routing [8]





Motivation
Architecture and Intuition
Network Metrics
Application Metrics
Performance Results
Motivation
Application QoS
Network QoC
Whether the communication path can support
any particular application delay, or bandwidth?
Ad Hoc QoS means to provide a set of
parameters in order to adapt application to the
quality of communication path while routing
through the network [7]
Architecture
AN ARCHITECTURE THAT SEPARATES [8]:
Application
QoS Classes
HARP
App. Metrics
Delay TPut BE
DDR
Network
Protocol stack
Path selection phase
Network Metrics:
QoC:
Power, buffer
Stability, # hops
QoS extension
Path Discovery phase
Network Metrics
Hop count  resource conservation
 Power level
Load balancing
 Buffer Level
 Stability Level

Trade-off between load balancing & resource conservation
Compute during path discovery using concave function
Reflect the quality of the communication paths
Map this quality to application metrics
Application Metrics
Service
App. Metrics Net. Metrics
1st Class
Delay
2nd Class
Throughput
3rd Class
Best-Effort
Legend
h : hop count
r : buffer size
c/(2h.(r-b)) b : buffer occupancy
c : nodes’ throughput
1/s
s : stability
h.(r-b)/c
Compute during path selection
Reflect the quality of service requirement
Avg. E2E Delay
Delay performance has significant improved
QoS metric is the key factor for the delay performance due
to its load balancing effect
10 sources
20 sources
30 sources
Packet Delivery Fraction
QoS metrics has no significant effect on PDF
Route discovery and route maintenance are the key factors for improving PDF
Deal with Traffic load/pattern and mobility model/rate
10 sources
20 sources
30 sources
ConclusionArchitecture
Pro-Network
Routing
Pro-Application
Topology management
Route determination
Quality of connectivity (QoC)
Quality of Service (QoS)
Conclusion
Topology management improves routing
Load balancing


HARP  QoS metrics
DDR  QoC metrics
Control flooding overhead


Forest  redundancy & collision
Query localization technique  scope
Scalability  zone abstraction
Conclusion
Routing requires:




Adaptive topology management
Load balancing
Congestion avoidance mechanisms
Neighboring information
Factors affecting routing performance

Network size, mobility rate and model, traffic load
and pattern, network density
Traffic locality vs. network size
Future Work



Optimal criteria of forest Construction
Introduce an adaptive routing mechanisms
Extend the QoS model to support metrics at
the link layer (e.g. SNR)
Publications
[1] N. Nikaein and C. Bonnet, “An Architecture for Improving
Routing and Network Performance in Mobile Ad Hoc Network”,
Kluwer/ACM MONET, 2003.
[2] N. Nikaein, H. Labiod, and C. Bonnet, “DDR-- Distributed
Dunamic Routing Algorithm for Mobile Ad Hoc Networks”,
MobiHoc, 2000.
[3] N. Nikaein, S. Wu, C. Bonnet and H. Labiod, “Designing
Routing Protocol for Mobile Ad Hoc Networks”, DNAC, 2000.
[4] N. Nikaein and C. Bonnet, “ Improving Routing and Network
Performance in MANET using Quality of Nodes”, WiOpt, 2003
Publications
[5] Navid Nikaein, C. Bonnet and Neda Nikaein, “HARP- Hybrid Ad
Hoc Routing Protocol ”, IST, 2001.
[6] Navid Nikaein, C. Bonnet, N. Akhtar and R. Tafazolli, “HARP-v2
Hybrid Ad Hoc Routing Protocol ”, To be submitted, 2003.
[7] N. Nikaein and C. Bonnet, “A Glance at Quality of Service
models in Mobile Ad Hoc Networks”,DNAC, 2002.
[8] N. Nikaein, C. Bonnet, Y. Moret and I. A. Rai, “LQoS- Layered
Quality of Service Model for Routing in Mobile Ad Hoc
Networks”, SCI, 2002.
[9] N. Nikaein and C. Bonnet, “ALM-- Adaptive Location
Management Model Incorporating Fuzzy Logic For Mobile Ad
Hoc Networks ”, Med-Hoc-Net, 2002.
Architecture
Problem Definition ?
Trade-off between routing overhead and
delay while maximizing network utilization
Trade-off between load balancing and
resource conservation
Separation between topology management
and route determination
What are the design elements of routing and
how they must interact ?
Zone Behaviors
As the number of zone increases, the overhead within a zone decreases but
the overhead between zones increases
Whatever the network density is, the zone diameter is bounded to 8
What is the optimal number of zones to achieve the minimum overall
overhead ? Mopt<N
Number of Zones
Size of Zones
Diameter of zones
Buffer Drop Distribution for
No/Low Mobility with High Load
Delay Distribution for
No and Low Mobility
Query Localization Technique
Offset= mobility x elapsed time
…
SRC
Src
Offset
dxR
RD_Offset
DST
Dst
Offset
Query Localization Technique
Offset= mobility x elapsed time
…
SRC
Src
Offset
dxR
RD_Offset
DST
Path_offset
Query Localization Technique
if (rd(x,dst)>rd(src,d))
Drop PREQ;
x
PREQ
else if (rd(x,dst)<TTL)
TTL=rd(x,dst);
d=k
…
PREQ
src
d=3
d=2
x
d=1
dst
QoS Mapping
IP QoS Class
Radio QoS Class
1st Class
Low delay/High dropping
IntServ
DiffServ
Guaranteed Expedited
Service
Forwarding
2nd Class
Controlled Assured
Medium delay/Medium dropping
Load
Forwarding
3rd Class
Best Effort Best Effort
High delay/Low dropping
Example


A path of lower hop count has higher delay,
because of high buffering delays.
The other path of a possibly higher hop count, but
lower delay. (also load balancing).
Stability Level




Node mobility a basic characteristic of ad hoc
networks.
A point of difference from wired networks.
Critical to capture this node mobility in the
routing protocol in order to determine stable,
reliable routes.
We propose:
stab( x) 
| N t0  N t1 |
| N t0  N t1 |
Nto: neighbors at time to.
Nt1: neighbors at time t1.
Stability Level
stab( x) 




| N t0  N t1 |
| N t0  N t1 |
0  stab(x)  1
stab (x) = 1 high stability, stab (x) = 0 low stability
Numerator: nodes that have remained in the
neighborhood of x.
High stability if none (few) of its neighbors
change, low stability if many (all) of its
neighbors change.
Stability

Example:
1
1
1
1/2
3/4
1
0
t0

t1
Stability also reflects connectivity. A large degree
node, in general, more stable.
NLM Evaluation of a Path


In path generation, NLM are propagated
through the nodes of generated paths.
For a path P = <s, n1, n2, …, nk, d>




P.hop = nP\{s} 1
P.power = minnP\{s, d} n.power
P.buffer= (nP\{s, d} n.buffer) / (P.hop - 1)
P.stability= minnP\{s} n.stability
Service differentiation
Class I
60%
Class II
30%
Class III
10%
Outgoing
traffic
Status Concept



A node broadcasts is QoS state itself.
This QoS state reflects node’s ability to act
as a router. If selfish, then ceases to act as a
router, doesn’t take part in routing protocol.
Since propagated by the node itself, the
possibility of lying. (malicious behavior)

pretend to be in selfish mode, to avoid being
chosen for forwarding.
Status Concept



A selfish node does not serve the network
(does not route), hence, fair that it receives
poor services from the network.
Status: the fraction of time a node has been
in unselfish mode to the network.
The status of node y at node x:
Nu [ y]
R[ y ] 
N[ y]
Nu [y] : number of y’s beacons in unselfish mode.
N [y] : total number of y’s beacons received.
Status Concept





How to prevent malicious behavior?
Give a status to each node, and give
incentive to a node to act as a router.
If a node acts as a router, then it is not in
selfish mode.
Prefer packets generated by unselfish nodes
while routing.
Hence, a node that has remained selfish,
receives poor services from the network.
DMPDC

Modify MRDC to adapt the infrastructure offered by
DDR in order to




Use DDR’s forest to broadcast Core Advertisement
message
Use DDR’s intra-zone routes



Improve bandwidth efficiency
Speed up link error detection and recovery
Reduce multicast tree maintenance cost
Benefit from DDR’s periodical intra-zone route update
Use DDR’s neighborhood knowledge to detect link
failure