Performance Analysis of Cluster Based Dissemination in VANET
Implementation Plan:
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Scenario 1: Using Gaussian Mixture Model (GMM)
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Step 1: Initially, we will construct a VANET Network with 120 vehicles , 4 RSU, 2 Base station and 1 Server
Step 2; Then, we simulate and collect the simulated data.
Step 3: Next, we Implement the Gaussian Mixture Model (GMM) clustering algorithms for dissemination:
Step 4: Next, we Develop cluster-based alert dissemination protocols utilizing the clusters formed by GMM.
Step 5: Next, we Implement AODV-based alert dissemination protocol for routing as a baseline.
Step 6: Finally, we plot performance metrics for the following
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 (%)
6.4: Number of vehicles vs. Cluster Stability(%)
6.5: Number of vehicles vs. Alert Dissemination Efficiency (%)
6.6: Number of vehicles vs. Communication Overhead (%)
Scenario 2: Using AMACAD
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Step 1: Initially, we will construct a VANET Network with 120 vehicles , 4 RSU, 2 Base station and 1 Server
Step 2; Then, we simulate and collect the simulated data.
Step 3: Next, we Implement the AMACAD clustering algorithms for dissemination:
Step 4: Next, we Develop cluster-based alert dissemination protocols utilizing the clusters formed by AMACAD.
Step 5: Next, we Implement AODV-based alert dissemination protocol for routing as a baseline.
Step 6: Finally, we plot performance metrics for the following
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 (%)
6.4: Number of vehicles vs. Cluster Stability(%)
6.5: Number of vehicles vs. Alert Dissemination Efficiency (%)
6.6: Number of vehicles vs. Communication Overhead (%)
Scenario 3: Using DBSCAN
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Step 1: Initially, we will construct a VANET Network with 120 vehicles , 4 RSU, 2 Base station and 1 Server
Step 2; Then, we simulate and collect the simulated data.
Step 3: Next, we Implement the DBSCAN clustering algorithms for dissemination:
Step 4: Next, we Develop cluster-based alert dissemination protocols utilizing the clusters formed by DBSCAN .
Step 5: Next, we Implement AODV-based alert dissemination protocol for routing as a baseline.
Step 6: Finally, we plot performance metrics for the following
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 (%)
6.4: Number of vehicles vs. Cluster Stability(%)
6.5: Number of vehicles vs. Alert Dissemination Efficiency (%)
6.6: Number of vehicles vs. Communication Overhead (%)
Scenario 4: Using Spectral Clustering
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Step 1: Initially, we will construct a VANET Network with 120 vehicles , 4 RSU, 2 Base station and 1 Server
Step 2; Then, we simulate and collect the simulated data.
Step 3: Next, we Implement the Spectral Clustering algorithms for dissemination:
Step 4: Next, we Develop cluster-based alert dissemination protocols utilizing the clusters formed by Spectral Clustering.
Step 5: Next, we Implement AODV-based alert dissemination protocol for routing as a baseline.
Step 6: Finally, we plot performance metrics for the following
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 (%)
6.4: Number of vehicles vs. Cluster Stability(%)
6.5: Number of vehicles vs. Alert Dissemination Efficiency (%)
6.6: Number of vehicles vs. Communication Overhead (%)
Software Requirements:
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1. Development Tool: OMNET++ 4.6 or above with Veins
2. Operating System: Windows 10 (64-bit) or above
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) Please understand that any modifications made to the confirmed implementation plan will not be made after the project development.
| Technology | Ph.D | MS | M.Tech |
|---|---|---|---|
| NS2 | 75 | 117 | 95 |
| NS3 | 98 | 119 | 206 |
| OMNET++ | 103 | 95 | 87 |
| OPNET | 36 | 64 | 89 |
| QULANET | 30 | 76 | 60 |
| MININET | 71 | 62 | 74 |
| MATLAB | 96 | 185 | 180 |
| LTESIM | 38 | 32 | 16 |
| COOJA SIMULATOR | 35 | 67 | 28 |
| CONTIKI OS | 42 | 36 | 29 |
| GNS3 | 35 | 89 | 14 |
| NETSIM | 35 | 11 | 21 |
| EVE-NG | 4 | 8 | 9 |
| TRANS | 9 | 5 | 4 |
| PEERSIM | 8 | 8 | 12 |
| GLOMOSIM | 6 | 10 | 6 |
| RTOOL | 13 | 15 | 8 |
| KATHARA SHADOW | 9 | 8 | 9 |
| VNX and VNUML | 8 | 7 | 8 |
| WISTAR | 9 | 9 | 8 |
| CNET | 6 | 8 | 4 |
| ESCAPE | 8 | 7 | 9 |
| NETMIRAGE | 7 | 11 | 7 |
| BOSON NETSIM | 6 | 8 | 9 |
| VIRL | 9 | 9 | 8 |
| CISCO PACKET TRACER | 7 | 7 | 10 |
| SWAN | 9 | 19 | 5 |
| JAVASIM | 40 | 68 | 69 |
| SSFNET | 7 | 9 | 8 |
| TOSSIM | 5 | 7 | 4 |
| PSIM | 7 | 8 | 6 |
| PETRI NET | 4 | 6 | 4 |
| ONESIM | 5 | 10 | 5 |
| OPTISYSTEM | 32 | 64 | 24 |
| DIVERT | 4 | 9 | 8 |
| TINY OS | 19 | 27 | 17 |
| TRANS | 7 | 8 | 6 |
| OPENPANA | 8 | 9 | 9 |
| SECURE CRT | 7 | 8 | 7 |
| EXTENDSIM | 6 | 7 | 5 |
| CONSELF | 7 | 19 | 6 |
| ARENA | 5 | 12 | 9 |
| VENSIM | 8 | 10 | 7 |
| MARIONNET | 5 | 7 | 9 |
| NETKIT | 6 | 8 | 7 |
| GEOIP | 9 | 17 | 8 |
| REAL | 7 | 5 | 5 |
| NEST | 5 | 10 | 9 |
| PTOLEMY | 7 | 8 | 4 |