A study of Intelligent Adaptive beaconing approaches on VANET Proposal Presentation Chayanin Thaina Advisor : 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) Avaliable from:

Comparison of MANET and VANET ParametersMANETVANET MobilityLowHigh Change in network topology SlowFrequently and fast Partitioned networkLowFrequently Moving pattern of nodes RandomConstrained 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 areaDense area High 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 overhead Beacon 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 = (w 1 x n)+(w 2 x m) s : Dense value, n : Number of neighbors, m : Number of buffer packets w1, 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

 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 movementDepending on surrounding vehicles’ movement Velocity Movement change Special vehicle AccelerationYaw rate Macroscopic scope Microscopic scope Vehicle Density Close-by vehicles Crossing vehicles …

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 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 : Dependent variable : Independent variable : 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

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

Output

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 HighwayUrban Density (veh/km)2,6,10,20,30,40,60,802,10,30,60,80 Speed of data dissemination (s) 1015

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