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A study of Intelligent Adaptive beaconing approaches on VANET
Proposal Presentation
Chayanin ThainaAdvisor : Dr.Kultida Rojviboonchai
MANET & VANET
Beaconing in VANET
Problems of using constant beaconing rate in VANET
Research on Adaptive beaconing rate in VANET
My Proposal
Future work
Group of mobile nodes No infrastructure Establish connectivity via multi-hop wireless
communication
Mobile Ad hoc Network (MANET)
Mobile Ad hoc network (MANET)
Vehicular Ad hoc Network (VANET)
Intervehicle communication VANET characteristics• Nodes move with high speed• High number of nodes• Frequently change in network topology
Vehicular Ad hoc Network (VANET)
Vehicular Ad hoc Network (VANET)
Avaliable from: http://www.car-to-car.org/
Comparison of MANET and VANET
Parameters MANET VANET
Mobility Low High
Change in network topology Slow Frequently and fast
Partitioned network Low Frequently
Moving pattern of nodes Random Constrained by road
Beaconing in VANET
Problems of using constant beaconing rate in VANET
Research on Adaptive beaconing rate in VANET
My Proposal
Future work
MANET & VANET
Beaconing in VANET
Vehicle • Discover neighbors• Exchange information
Information may contain • nodeID• vehicle velocity• Position• acknowledgement e.g.
Most of protocols in VANET using constant beaconing rate
Examples of protocols (using constant beaconing rate)
Routing protocol• VADD : Vehicle-assisted data delivery in vehicular Ad hoc networks (IEEE Trans. on vehicular tech., 2008)
- Beacon interval : 0.5s Broadcasting protocol
• AckPBSM : Acknowledge Parameterless broadcast protocol in static to highly mobile ad hoc networks
- Reliable and efficient broadcasting vehicular ad hoc networks (VTC, 2009) - Beacon interval : 0.5s• DV-Cast : Distributed Vehicular Broadcast Protocol for
Vehicular Ad-hoc Networks (IEEE Wireless communication, 2010)
- Beacon interval : 1s
Problems of using constant beaconing rate in VANET
Research on Adaptive Beaconing in VANET
My Proposal
Future work
MANET & VANET
Beaconing in VANET
Problems of using constant beaconing rate in VANET
Sparse area Dense areaHigh beaconing rate
- Faster neighbor discovery
- Collision problem- Decrease reliability- High beacon overhead
Low beaconing rate
- Decrease reliability - Increase reliability- Lower beacon overhead
Problems of using constant beaconing rate in VANET
Reliability Beacon interval (s)
Problems of using constant beaconing rate in VANET
Beacon overheadBeacon interval (s)
Research on Adaptive beaconing rate in VANET
My Proposal
Future work
MANET & VANET
Beaconing in VANET
Problems of using constant beaconing rate in VANET
Research on Adaptive Beaconing in VANET
CAR: Connectivity-Aware Routing in Vehicular Ad Hoc Networks (Infocom, 2007) Improving Neighbor Localization in Vehicular Ad Hoc Networks to Avoid Overhead from Periodic Messages (GLOBECOM, 2009) Efficient Beacon Solution for Wireless Ad-Hoc
Networks (JCSSE, 2010) Exploration of adaptive beaconing for efficient
intervehicle safety communication (IEEE Network, 2010)
Connectivity-Aware Routing in Vehicular Ad Hoc Networks (CAR)
Proposed• Find connected paths between source and
destination pairs• “Guards” help to track the current position
Methodology• Adaptive beaconing rate
- Beaconing interval is changed according to the number of neighbors- Calculate beacon interval
0.5s*w*number of neighbors
Advantage• Simple solution
Disadvantage• Considered only the number of neighbors
Connectivity-Aware Routing in Vehicular Ad Hoc Networks (CAR)
Improving Neighbor Localization in Vehicular Ad Hoc Networks to Avoid Overhead from Periodic Messages
Proposed• Improve accuracy of the localization of
neighboring vehicles• Decrease number of beacons
Methodology• Beacon rate adaptation based on differences in
predicted position• Use last beacon message to estimate position • Send next beacon
- When the difference between the predicted and actual position is greater than
Advantage• Position predicted increase the accuracy of
the localization of neighbors
Disadvantage• Use GPS information• Did not consider node’s environment
Improving Neighbor Localization in Vehicular Ad Hoc Networks to Avoid Overhead from Periodic Messages
Efficient Beacon Solution for Wireless Ad-Hoc Networks
Proposed• Adaptive beaconing schemes
- Save beacon overhead - Maintain accurate local information
Methodology• Adapt beacon based on number of neighbors and
number of buffered packets
s = (w1 x n)+(w2 x m)
s : Dense value, n : Number of neighbors, m : Number of buffer packetsw1, w2 : Weight value of number of neighbors and number of buffer packets
Efficient Beacon Solution for Wireless Ad-Hoc Networks
LIA : Linear Adaptive Algorithm STA : Step Adaptive Algorithm
𝐋𝐈𝐀 : 𝑓 (𝑠 )=min(𝑀𝑖𝑛𝐼𝑛𝑣+ (𝑐 𝑥 𝑠) ,𝑀𝑎𝑥𝐼𝑛𝑣)STA :
Advantage• Did not use GPS information
Disadvantage• Not flexible
- Considered only in case of the fastest speed of data dissemination
Efficient Beacon Solution for Wireless Ad-Hoc Networks
Exploration of adaptive beaconing for efficient intervehicle safety communication
Proposed• Control the offered load • Adjust the beacon frequency dynamically to the current traffic situation• Maintain appropriate accuracy
Methodology• 2 categories of schemes
1. Depending on the vehicle’s own movement
2. Depending on the surrounding vehicles’ movement
• Combination of Schemes
Exploration of adaptive beaconing for efficient intervehicle safety communication
Situation-adaptive beaconing
Depending on own movement Depending on surrounding vehicles’ movement
Velocity
Movement change
Specialvehicle
Acceleration Yaw rate
Macroscopic scope
Microscopic scope
VehicleDensity
Close-byvehicles
Crossingvehicles
…
Exploration of adaptive beaconing for efficient intervehicle safety communication
Advantage• Considered several schemes for adaptation of
beacon rate
Disadvantage• Only a theoretical analysis• Did not show how to implement • Did not show the result
Paper conclusion
CAR
Improving Neighbor Localization in Vehicular Ad Hoc Networks to Avoid Overhead from Periodic Messages
Efficient Beacon Solution for Wireless Ad-Hoc Networks
Exploration of adaptive beaconing for efficient intervehicle safety communication
Parameters used in calculation
- Number of neighbors
- Vehicle position- Speed- Direction
- Number of neighbors- Number of packets
- Velocity- Acceleration- Yaw rate-Emergency/ Regular vehicle- Vehicle density- Special situation
Selection mechanisms Linear
function Predicted position- Linear Adaptive Algorithm (LIA)- Step Adaptive Algorithm (STA)
X
GPS X X
My Proposal
Future work
MANET & VANET
Beaconing in VANET
Problems of using constant beaconing rate in VANET
Research on Adaptive Beaconing in VANET
Idea of my beacon approaches Adaptation beacon rate by considering node’s
environment e.g.• Number of neighbors• Number of messages
Number of neighbors +Number of messages
High
Beacon rate
Low
Low
Beacon rate
High
Consider the requirement of speed of data dissemination in each application
Number of neighbors +Number of messages
Goals of my beacon approaches Reduce beacon overhead Maintain • Reliability• Retransmission
Provide the speed of data dissemination according to the requirement of each
application
Idea of my beacon approaches
Determination of a math model by using• Linear regression analysis
Linear regression
Idea of my beacon approaches
Use the technique of Artificial Intelligence (AI) to adapt beacon rate• Machine Learning (a branch of AI)
e.g. K-nearest neighbor
Linear regression analysis
Finding relationship between independent variables and a dependent variable
bxay ˆ
y: Dependent variable x: Independent variableba, : Regression coefficients
Linear regression analysis
Adaptive beaconing rate• Dependent variable
- Beacon interval • Independent variable
- Number of neighbors + number of messages
Instance-based learning• Approximate real-valued or discrete-valued
target function• Store and all training examples
K-nearest neighbor• Assume all instances corresponding to points in
the n-dimensional space
K-nearest neighbor
))(,( ii xfx
• If has query instance
- Nearest neighbors are defined by Euclidean distance
• Distance-weighted k-nearest neighbor- Weigh each k-nearest neighbor according to their distance to the query point
K-nearest neighbor
qx
n
rjrqrjq xaxaxxd
1
2))()((),(
qx
2),(
1
jqi xxdw
K-nearest neighbor• Output
�� (𝑥 𝑞)=∑𝑖=1
𝑘
𝑤𝑖 𝑓 (𝑥𝑖)
∑𝑖=1
𝑘
𝑤𝑖
Case study DECA : Density-Aware Reliable Broadcasting in Vehicular Ad Hoc Networks (ECTI-CON, 2010)
Reliable broadcast protocol Store and forward solution Exchange beacon message (Use Linear Adaptive Algorithm :LIA)• Beacon information contains
- Local density- Identifier of received message
DECA
Broadcast message• Sender select the forwarder from its neighbor list
- Neighbor with the highest density will be selected• Selected node rebroadcast the message
immediately• Other neighbors (which are not selected)
- Store the message and set waiting timeout• In case the selected node doesn’t rebroadcast
the message- Other neighbors will rebroadcast the message
DECA
Simulation Network Simulation : NS-2.34 Traffic Simulation• Trace generator : SUMO (Simulation of Urban
MObility)• XML convertor to NS2 trace : TraNS
Vehicles• Maximum speed : 120 km/h
Message : 1 message
Simulation Scenario 3x3 km. with 2 lanes
Urban Scenario
4x4 km. with 4 lanes
Highway Scenario
Simulation
Highway Urban
Density (veh/km) 2,6,10,20,30,40,60,80 2,10,30,60,80
Speed of data dissemination (s) 10 15
Simulation Metrics• Reliability
- percentage number of received node to number of total node
• Beacon overhead- bandwidth that has been used for every beacon (bytes/node/message)
• Retransmission- bandwidth that has been used for data transmission
(bytes/node/message)
• Speed of data dissemination- percentage of number of node that received
message at time (t)
Simulation result (Highway) 1 message (Reliability)
Simulation result (Highway) 1 message (Beacon overhead)
Simulation result (Highway) 1 message (Retransmission)
Simulation result (Highway) 1 message 2,6,10,20 veh/km (Speed of data dissemination)
Simulation result (Highway) 1 message 30,40,60,80 veh/km (Speed of data dissemination)
Simulation result (Urban) 1 message (Reliability)
Simulation result (Urban) 1 message (Beacon overhead)
Simulation result (Urban) 1 message (Retransmission)
Simulation result (Urban) 1 message 2,10,30 veh/km (Speed of data dissemination)
Simulation result (Urban) 1 message 60,80 veh/km (Speed of data dissemination)
Future work
MANET & VANET
Beaconing in VANET
Problems of using constant beaconing rate in VANET
Research on Adaptive beaconing rate in VANET
My Proposal
Future work More than one concurrent messages in
simulation Simulate in real scenario map Analyze advantage and disadvantage of each
methodology Determine the method that can adjust
beaconing rate more efficiently