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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. Outline. Characteristics & Limitations. Applications. MANETs. - PowerPoint PPT Presentation
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1
Adjusted Counter-Based Broadcast for Wireless Mobile Ad hoc Networks
Sara Omar al-Humoud
Department of Computing Science
University of Glasgow
Supervisors: Dr. L.M. Mackenzie and Dr. M. Ould-Khaoua
First Year Viva
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
4
Introduction
• MANETs?
• Decentralized
• Dynamic topology
• Radio communication
• Energy constrained
MANETs Characteristics and Limitations
5
Introduction
• Military applications
• Collaborative and distributed computing
• Emergency operations
• Inter-Vehicle Communications
• Hybrid wireless networks
MANET Applications
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
7
Introduction
• 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)
Routing in MANET
8
Introduction
• Source-initiated On-demand Routing (reactive)– 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)
Routing in MANET
9
Introduction
• 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)
Routing in MANET
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
11
Introduction
• 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
Broadcasting Applications
12
Introduction
• Flooding may lead to– Redundancy
x Consume limited bandwidth
– Contentionx Increase in delay
– Collisionx High packet loss rate
– Broadcast storm problem!
Broadcasting Applications
0
10
20
30
40
50
60
70
80
90
0 1 2 3 4 5 6 7 8 9 10
Number of Nodes
Nu
mb
er o
f M
essa
ges
f(n) = n2 – 2n + 1
Outline
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
2.Related work
14
Related work
• 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
Probabilistic Broadcasting Methods
Receiver rebroadcast
decision
Simple Implementation RD based on instantaneous information from broadcast msgs
15
Related work
• Reliable Broadcast
• Self-pruning
• Scalable broadcasting
• Dominant Pruning
• Cluster-based
Deterministic Broadcasting Methods
Sender rebroadcast
decision
Elaborate Implementation Rebroadcast decision based on neighbourhood study
16
Related work
1. Counter-based broadcast
– Adaptive Counter-based broadcast
2. Color-based broadcast
3. Distance-aware counter-based broadcast
Counter-Based related Broadcasting Methods
17
Related work
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
Counter-Based related Broadcasting Methods
18
Related work
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.
Counter-Based related Broadcasting Methods
c1 c2 c3
19
Related work
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.
Counter-Based related Broadcasting Methods
Outline
2.Related work
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
3.Motivations and objectives
21
Motivations and objectives
• 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.
Related work limitations - overhead
22
Motivations and objectives
• 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
Related work limitations - overhead
23
Motivations and 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
Objectives
24
Motivations and 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
Objectives
Avg
Sparse DenseNeighbourhoodDensity
25
Motivations and 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
Objectives
Sparse DenseMedium
Min Max
NeighbourhoodDensity
Outline
2.Related work
3.Motivations and objectives
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
4.Thesis Statement
Thesis Statement
27
Go to Thesis Statement
Cont
28
Thesis Statement
• 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.
T1
29
Thesis Statement
• 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.
T2
30
Thesis Statement
• 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 counter-based AODV protocols. Additionally, it will perform better than probabilistic and adjusted probabilistic AODV routing protocols.
T3
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
Contributions
32
Algorithms
Cont
Adjusted_Counter_Based_Broadcast_Algorithm
Pre: avg is average number of neighborsa broadcast packet m at node X is heard
Post: rebroadcast the packet or drop it, according to the algorithm
Get the Broadcast IDGet degree n of node XSet RADc = 1If n < avg then
Sparse network
threshold = c1;
Else
Dense network
threshold = c2;
End if While (RAD) Do
If (same packet heard)
Increment c
End whileIf (counter > threshold)
drop packet
exit algorithm
End IfSubmit the packet for transmission End Adjusted_Counter_Based_Broadcast_Algorithm
Highly_Adjusted_Counter_Based_Broadcast_Algorithm
Pre: avg is average number of neighborsmin is minimum number of neighborsmax is maximum number of neighborsa broadcast packet m at node X is heard
Post: rebroadcast the packet or drop it, according to the algorithm
Get the Broadcast IDGet degree n of node XSet RADc = 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 whileIf (counter > threshold)
drop packet
exit algorithm
End If
Submit the packet for transmission
End Highly_Adjusted_Counter_Based_Broadcast_Algorithm
35
Contributions
• 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.
Methodology
36
Contributions
• 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.
Performance measures
37
Contributions
• 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
Assumptions
Contributions
38
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
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
6.Tentative work plan
Tentative work plan
40
Assumptions
ID Task End Date
1 Submit my first year report July /2007
2 Experiment with ns2 simulator August /2007
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 August /2008
11 Submit my dissertation July /2009
12 Do my final year Viva August /2009
14 Thesis correction and final submission Oct /2009
Outline
2.Related work
3.Motivations and objectives
4.Thesis Statement
6.Tentative work plan
7.Thesis structure
MANETs
Routing
Broadcasting
Characteristics & Limitations
Applications
1.Introduction Proactive
Reactive
Hybrid
Probabilistic
Algorithms
Methodology
Deterministic
5.Contributions
Counter Related
Simulation study
Measures
Assumptions
ACB
HACB
42
Thesis structure
Chapter 1: IntroductionMANET
Broadcasting
Related work
Motivation
Contribution
Thesis statement
Chapter 2: Background and related workIntroduction
Fixed counter-based broadcasting
Chapter 3: Adjusted Counter-based BroadcastingIntroduction
Adjusted counter-based broadcasting
Analysis on Adjusted counter-based
Comparison between Fixed and Adjusted Counter-based
Chapter 4: Highly Adjusted Counter-based BroadcastingIntroduction
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
43
Questions
EAC
44
(a) (b)