Analysis of Node Selection Alert Message in Vehicular Network

Performance Analysis of Node Selection & Alert Message Dissemination in Vehicular Networks

Implementation plan:
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Scenario 1: (Q learning based dissemination)
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Step 1: Initially, we will construct a VANET Network with 50 vehicles , 2 RSU and 1 Server.

Step 2: Then, we will configure and analyze the RSU coverage area as a state space distinguishing road zones and non-road zones.

Step 3: Next, we will apply the flood-fill algorithm to exclude non-road zones and define valid rebroadcast areas.

Step 4: Next, we will estimate initial rebroadcast vehicle positions by calculating polar coordinates with RSU transmission range as radius.

Step 5: Next, we will implement the Q-learning mechanism where anticlockwise and clockwise movements update the state-action values based on coverage rewards for for efficient message dissemination

Step 6: Finally, we plot performance for the following metrics:

6.1: Number of vehicles vs. Throughput (Mbps)

6.2: Number of vehicles vs. End to End Delay (ms)

6.3: Number of vehicles vs. Packet Delivery Ratio (%)

Scenario 2 : (AODV based routing protocol)
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Step 1: Initially, we will construct a VANET Network with 50 vehicles , 2 RSU and 1 Server.

Step 2: Then, we will configure and analyze the RSU coverage area as a state space distinguishing road zones and non-road zones.

Step 3: Next, we will apply the flood-fill algorithm to exclude non-road zones and define valid rebroadcast areas.

Step 4: Next, we will estimate initial rebroadcast vehicle positions by calculating polar coordinates with RSU transmission range as radius.

Step 5: Next, we will implement the AODV Based Routing protocol for efficient message dissemination.

Step 6: Finally, we plot performance for the following metrics:

6.1: Number of vehicles vs. Throughput (Mbps)

6.2: Number of vehicles vs. End to End Delay (ms)

6.3: Number of vehicles vs. Packet Delivery Ratio (%)

Software requirement:
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1. Development Tool: OMNET++ 4.6 with Veins and SUMO
2. Operating System: Windows 11 (64-bit)

Note
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1) If the plan does not meet your requirements, provide detailed steps, parameters, models, or expected results in advance. Once implemented, changes won’t be possible without prior input; otherwise, we’ll proceed as per our implementation plan.

2) If the plan satisfies your requirement, Please confirm with us.

3) Project based on Simulation only, not a real time project.

4) If you have any changes in the Dataset , kindly provide before implementation.

5) Please understand that any modifications made to the confirmed implementation plan will not be made after the project development.

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