Transcript FYV-v3 - School of Computing Science

Adjusted Counter-Based Broadcast for
Wireless Mobile Ad hoc Networks
Sara Omar al-Humoud
Department of Computing Science
University of Glasgow
First Year Viva
Supervisors:
Dr. L.M. Mackenzie and Dr. M. Ould-Khaoua
1
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Introduction
MANETs Characteristics and Limitations
• MANETs?
• Decentralized
• Dynamic topology
• Radio communication
• Energy constrained
4
Introduction
MANET Applications
• Military applications
• Collaborative and distributed
computing
• Emergency operations
• Inter-Vehicle Communications
• Hybrid wireless networks
5
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Introduction
Routing in MANET
• Table Driven Routing Protocols (Proactive)
– Destination-Sequenced Distance-Vector Routing (DSDV)
– Clusterhead Gateway Switch Routing (CGSR)
– Global state routing (GSR)
– Source-tree adaptive routing (STAR)
– Fisheye state routing (FSR)
– Distance routing effect algorithm for mobility (DREAM)
– Optimised link state routing (OLSR)
– Topology broadcast reverse path forwarding (TBRPF)
– Wireless Routing Protocol (WRP)
7
Introduction
Routing in MANET
• Source-initiated On-demand Routing (reactive)
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Ad-hoc On-Demand Distance Vectoring (AODV)
Dynamic Source Routing (DSR)
Temporally-Ordered Routing Algorithm (TORA)
Associativity Based Routing (ABR)
Light-weight mobile routing (LMR)
Routing on-demand acyclic multi-path (ROAM)
Relative distance micro-discovery ad hoc routing (RDMAR)
Location-aided routing (LAR)
Ant-colony-based routing algorithm (ARA)
Flow oriented routing protocol (FORP)
Cluster-based routing protocol (CBRP)
Signal Stability Routing (SSR)
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Introduction
Routing in MANET
• Hybrid routing protocols
– Zone routing protocol (ZRP)
– Zone-based hierarchical link state (ZHLS)
– Scalable location update routing protocol (SLURP)
– Distributed spanning trees based routing protocol (DST)
– Distributed dynamic routing (DDR)
9
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Introduction
Broadcasting Applications
• Discovering neighbours
• Collecting global information
• Addressing
• Helping in multicasting and Unicast
– Route discovery, route reply
– in on-demand routing protocols like DSR, AODV to broadcast
control messages.
• Conventionally broadcast is done through flooding
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Introduction
Broadcasting Applications
• Flooding may lead to
– Redundancy
90
80
x Consume limited bandwidth
x Increase in delay
– Collision
x High packet loss rate
– Broadcast storm
problem!
Number of Messages
– Contention
70
60
50
40
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20
10
0
0
1
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5
6
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Number of Nodes
f(n) = n2 – 2n + 1
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10
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Related work
Probabilistic Broadcasting Methods
• Probability-based
– Rebroadcast with probability P
• Counter-based
– Rebroadcast if the node received less
than Cth copies of the msg
• Location-based
– Rebroadcast if the area within the
node’s range that is yet to be covered by
the broadcast > Ath
• Distance-based
– Rebroadcast if the node did not receive
the msg from another node at a distance
less than Dth
Receiver
rebroadcast
decision
Simple Implementation
RD based on instantaneous information from broadcast msgs
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Related work
Deterministic Broadcasting Methods
• Reliable Broadcast
• Self-pruning
• Scalable broadcasting
• Dominant Pruning
• Cluster-based
Sender
rebroadcast
decision
Elaborate Implementation
Rebroadcast decision based on neighbourhood study
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Related work
Counter-Based related Broadcasting Methods
1. Counter-based broadcast
– Adaptive Counter-based broadcast
2. Color-based broadcast
3. Distance-aware counter-based broadcast
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Related work
Counter-Based related Broadcasting Methods
1- Counter-based broadcast
•
Scheme:
– When receiving a message:
• a counter c is set to keep track of number of duplicate messages
received.
• Random Assessment Delay (RAD) timer is set.
• When the RAD timer expires the counter is tested against a fixed
threshold value C, broadcast is inhibited if c ≥ C.
•
Remarks:
– The threshold is fixed: scores high efficiency only when used with
homogeneous density networks; when the network is sparse a high
threshold is used and when dense low threshold value.
Adaptive Counter-based broadcast
• Threshold = C(n) where n is the number of neighbors
• The function C(n) is undefined yet
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Related work
Counter-Based related Broadcasting Methods
2- Color-based broadcast
•
Scheme:
– each broadcast node selects a color from a set of η colors which it writes to a
color-field present in the broadcast message.
– all nodes which hear the message rebroadcast it unless they have heard all η
colors by the time a random timer expires.
•
Remarks:
– With the added overhead, we may end with a bad case:
– E.g. a node receive 3 messages with only c1 and this node will still
rebroadcast the message.
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c1
c2
c3
Related work
Counter-Based related Broadcasting Methods
3- Distance-aware counter-based broadcast
•
Scheme:
– Similar to the counter-based scheme in addition to:
• Two distinct RADs are applied to the border and interior nodes
• SRAD to border nodes
• LRAD to interior nodes
•
Remarks:
– The use of distance as an enhancement factor to the original counter-based
may be degraded knowing that real networks transmissions will be affected
by obstacles.
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Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Motivations and objectives
Related work limitations - overhead
• Area-based scheme
– Rely on GPS
• Deterministic approaches
– High time overhead
– High number of control messages exchanged to broadcast
one packet
– it demands accurate neighbourhood information and cannot
ensure the coverage with outdated topology information.
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Motivations and objectives
Related work limitations - overhead
• Counter-based schemes
– Fixed counter-based
• Threshold = c
– Adaptive counter-based
• Threshold = C(n) where n is the number of neighbors
• The function C(n) is undefined yet
– Color-based
• Used with homogeneous density networks
• Rebroadcast when many duplicates received by the a partial set
of colors
– Distance-aware counter-based
• Distance estimated by signal strength
• Not considering obstacle existence
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Motivations and objectives
Objectives
• Adjusted Counter-Based (ACB)
• Highly Adjusted Counter-Based (HACB).
• Counter-Based AODV
• Adjusted Counter-Based AODV
• Highly Adjusted Counter-Based AODV
• Study the superiority of our proposed schemes to
the probabilistic broadcasting
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Motivations and objectives
Objectives
• Adjusted Counter-Based (ACB) Broadcast
– Based on the original counter-based scheme
– Add the ability to decide the counter according to
neighbourhood density
– Neighbourhood density is divided according to the Average
number of neighbours into:
• Density1: Sparse
• Density2: Dense
Neighbourhood
Density
Sparse
Dense
Avg
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Motivations and objectives
Objectives
• Highly Adjusted Counter-Based (HACB) Broadcast
– Neighbourhood density is divided according to the Max and
Min number of neighbours into:
• Density1: Sparse
• Density2: Medium
• Density3: Dense
– Adding the average as a discriminator will divide the
neighbourhood density into four groups and will reveal a
better adjustment
Neighbourhood
Density
Sparse
Medium
Min
Dense
Max
25
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Thesis Statement
Go to Thesis
Statement
Cont
27
Thesis Statement
T1
• T1. While most previous studies have used a fixed
counter threshold for rebroadcasting irrespective of
the node status, this research proposes two new
counter-based algorithms that dynamically adjust the
counter threshold as per the node’s neighbourhood
distribution and node movement using one-hop
neighbourhood information. Employing neighbourhood
information in counter threshold decision will enhance
the existing fixed counter-based flooding in terms of
reachability, saved rebroadcast and delay.
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Thesis Statement
T2
• T2. The Adjusted Counter-Based (ACB) uses the
average number of neighbour to dynamically adjust
the threshold value to adapt to either sparse or dense
network. Moreover, when incorporated in the Ad hoc
On-Demand Distance Vector (AODV) routing protocol;
one of the well-known and widely studied routing
protocols over that past few years, ACB will perform
better than both standard and fixed counter-based
AODV protocols.
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Thesis Statement
T3
• T3. The Highly Adjusted Counter-Based (HACB) uses
three items of derived neighbourhood information the
maximum, the minimum in addition to the average
number of neighbours to dynamically adjust the
threshold value. HACB is better than ACB however,
perhaps with an added complexity. Moreover, when
incorporated in the AODV routing protocol; HACB will
perform better than both standard and fixed counterbased AODV protocols. Additionally, it will perform
better than probabilistic and adjusted probabilistic
AODV routing protocols.
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Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Contributions
Algorithms
Cont
32
Adjusted_Counter_Based_Broadcast_Algorithm
Pre:
avg is average number of neighbors
a broadcast packet m at node X is heard
Post: rebroadcast the packet or drop it, according to the algorithm
Get
Get
Set
c =
If
the Broadcast ID
degree n of node X
RAD
1
n < avg then
Sparse network
threshold = c1;
Else
Dense network
threshold = c2;
End if
While (RAD) Do
If (same packet heard)
Increment c
End while
If (counter > threshold)
drop packet
exit algorithm
End If
Submit the packet for transmission
End Adjusted_Counter_Based_Broadcast_Algorithm
Highly_Adjusted_Counter_Based_Broadcast_Algorithm
Pre:
avg is average number of neighbors
min is minimum number of neighbors
max is maximum number of neighbors
a broadcast packet m at node X is heard
Post: rebroadcast the packet or drop it, according to the algorithm
Get the Broadcast ID
Get degree n of node X
Set RAD
c = 1
If
n < min then
threshold = c1;
Else
If
n < max then
threshold = c2;
Else
threshold = c3;
End if
End if
While (RAD) Do
If (same packet heard)
Increment c
End while
If (counter > threshold)
drop packet
exit algorithm
End If
Submit the packet for transmission
End Highly_Adjusted_Counter_Based_Broadcast_Algorithm
Contributions
Methodology
• Simulation study
– First study considers a static network, using a Null MAC to
evaluate and compare our proposed algorithms to simple
flooding, the worst case.
– Second study considers the network under two sources of
instability:
• Mobility: changeable node speed.
• Congestion: variable quantities of packets originated per second.
– Third study considers a combination of variable node
density, node speed, and congestion.
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Contributions
Performance measures
• Reachability
– r/e, where r is the number of hosts receiving the broadcast
packet and e is the number of mobile hosts that are
reachable, directly or indirectly, from the source host .
• Saved Rebroadcast
– (r − t)/r, where r is the number of hosts receiving the
broadcast message, and t is the number of hosts that actually
transmitted the message.
• Average latency
– the interval from the time the broadcast was initiated to the
time the last host finished its rebroadcasting.
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Contributions
Assumptions
• Simulate a university campus with the
following assumptions:
– Existence of pedestrians and vehicles equipped with
IEEE 802.11 wireless transceivers
– Speed:
• walk speed of 1 m/sec with appropriate pose times to vehicles having
a maximum speed of 70 km/hour
– Area:
• First study: open unobstructed
• Second study: open with obstacles
– Mobility:
• First study: Random way point (RWP) mobility model
• Second study: Realistic Mobility Model
– We assume that a host can detect duplicate broadcast
messages.
– Assume that nodes have sufficient power to function
properly throughout the simulation time
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Contributions
Simulation parameters
Simulation parameter
Value
Simulator
ns-2 version (2.31)
Network Area
1500 x 1500 meter
Transmission range
100 meter
Data Packet Size
64 bytes
Node Max. IFQ Length
50
Simulation Time
500 sec
Pause Times
0, 10, 20, 40 sec
Number of Trials
10
MAC layer protocol
IEEE 802.11
Mobility model
Random waypoint model, Realistic Mobility Model
Traffic Type
CBR (Constant Bit Rate)
Channel Bandwidth
2Mb/sec
Confidence Interval
95%
Number of Nodes
20, 40, 50, 60, 80, 100
Packet Rate
10, 20, 40, 60, 80 100, 150 packets per sec
Counter threshold pairs
ACB: [2,3], [2,4], [3,4], HACB [2,3,4]
Node Max. Speed
1, 5, 10, 15, 20 m/sec
38
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Tentative work plan
Assumptions
ID
Task
End Date
1
Submit my first year report
July /2007
2
Experiment with ns2 simulator
3
Develop adaptive counter-based (ACB) scheme
Nov /2007
4
Compare ACB with counter-based (CB) scheme
Dec /2007
5
Develop Highly adaptive counter-based (HACB) scheme
Jan /2008
6
Develop Adaptive counter-based AODV
Mar /2008
7
Develop Highly Adaptive counter-based AODV
May /2008
8
Develop a realistic mobility model for ACB and HACB
June /2008
9
Submit my second year report
July /2008
10
Write up for my Ph.D. dissertation
11
Submit my dissertation
12
Do my final year Viva
14
Thesis correction and final submission
August /2007
August /2008
July /2009
August /2009
Oct /2009
40
Outline
Characteristics &
Limitations
MANETs
1.Introduction
Applications
Routing
Proactive
Broadcasting
Reactive
Hybrid
2.Related work
Probabilistic
3.Motivations
and objectives
Deterministic
Counter Related
4.Thesis Statement
ACB
5.Contributions
Algorithms
HACB
Methodology
Simulation study
6.Tentative work plan
Measures
Assumptions
7.Thesis structure
Thesis structure
Chapter 1: Introduction
MANET
Broadcasting
Related work
Motivation
Contribution
Thesis statement
Chapter 2: Background and related work
Introduction
Fixed counter-based broadcasting
Chapter 3: Adjusted Counter-based Broadcasting
Introduction
Adjusted counter-based broadcasting
Analysis on Adjusted counter-based
Comparison between Fixed and Adjusted Counter-based
Chapter 4: Highly Adjusted Counter-based Broadcasting
Introduction
Highly Adjusted counter-based broadcasting
Analysis on Highly Adjusted counter-based
Comparison between Adjusted and Highly Adjusted Counter-based
Chapter 6: Performance Evaluation of AODV with Adjusted Counter-based Route Discovery
Chapter 7: Performance evaluation of Counter-Based with Real mobility model
Chapter 8: Conclusions and Future Work
42
Questions
43
EAC
(a)
(b)
44