Performance Analysis of IS-IS Metrics and Segment Routing

Performance Analysis of IS-IS Metrics and Segment Routing

Implementation plan:

Scenario 1: (SDN-based Segment Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs, and 1 SDN Controller.

Step 2: Next, we simulate the network and collect network data such as Send/rec packets, distance, vehicle speed, and interface type from all nodes.

Step 3: Next, we enable SDN-based Segment Routing, where the controller dynamically assigns optimized IS-IS metrics to select the best routing paths based on collected data.

Step 4: Next, we predict the link lifetime for V2V and V2I links using distance, speed, and radio range information based on collected data.

Step 5: Next, we calculate link quality and raw IS-IS metrics, apply interface weighting and hysteresis smoothing, and cap the metric values based on collected data.

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

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Scenario 2: (Default AODV Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs.

Step 2: Next, we enable AODV Routing, and collect network data.

Step 3: Finally, we plot performance for the following metrics:

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Scenario 3: (Default OLSR Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs.

Step 2: Next, we enable OLSR Routing, and collect network data.

Step 3: Finally, we plot performance for the following metrics:

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Scenario 4: (SDN-based MPLS With AODV Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs, and 1 SDN Controller.

Step 2: Next, we simulate the network and collect network data such as Send/rec packets, distance, vehicle speed, and interface type from all nodes.

Step 3: Next, we enable MPLS over AODV Routing, where the controller dynamically assigns optimized IS-IS metrics to select the best routing paths based on collected data.

Step 4: Next, we predict the link lifetime for V2V and V2I links using distance, speed, and radio range information based on collected data.

Step 5: Next, we calculate link quality and raw IS-IS metrics, apply interface weighting and hysteresis smoothing, and cap the metric values based on collected data.

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

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Scenario 5: (SDN-based MPLS With OLSR Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs, and 1 SDN Controller.

Step 2: Next, we simulate the network and collect network data such as Send/rec packets, distance, vehicle speed, and interface type from all nodes.

Step 3: Next, we enable MPLS over OLSR Routing, where the controller dynamically assigns optimized IS-IS metrics to select the best routing paths based on collected data.

Step 4: Next, we predict the link lifetime for V2V and V2I links using distance, speed, and radio range information based on collected data.

Step 5: Next, we calculate link quality and raw IS-IS metrics, apply interface weighting and hysteresis smoothing, and cap the metric values based on collected data.

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

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Scenario 6: (Default MPLS With AODV Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs.

Step 2: Next, we simulate the network using fixed IS-IS metrics for interfaces, for V2I metric will be 100 and for V2V metric will be 200.

Step 3: Next, we enable MPLS over AODV Routing, where MPLS selects the best routing paths based on link metrics (Loose MPLS).

Step 4: Finally, we plot performance for the following metrics:

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Scenario 7: (Default MPLS With OLSR Routing Protocol)

Step 1: Initially, we will construct a VANET Network with 50 Vehicles, 2 RSUs.

Step 2: Next, we simulate the network using fixed IS-IS metrics for interfaces, for V2I metric will be 100 and for V2V metric will be 200.

Step 3: Next, we enable MPLS over OLSR Routing, where MPLS selects the best routing paths based on link metrics (Loose MPLS).

Step 4: Finally, we plot performance for the following metrics:

6.1: Number of Vehicles vs. End-to-End Delay (ms)
6.2: Number of Vehicles vs. Packet Delivery Ratio (%)
6.3: Number of Vehicles vs. Throughput (Mbps)
6.4: Number of Vehicles vs. Routing Overhead (%)
6.5: Number of Vehicles vs.  Number of Retransmissions

Software requirement:

1. Development Tool: OMNET++ 4.6 or above with Veins and SUMO
2. Operating System: Ubuntu 22.04 (64-bit) LTS or Above

Note:

1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance. Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.

2) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.

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

4) Project based on Simulation only.

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