Performance Analysis of QoS Aware Adaptive 5G Network Slicing for Healthcare IoT
Implementation plan:
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Scenario 1: (Without Network Slicing):
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Step 1: Initially, we constructed a 5G network with 50 Sensor nodes, 2 Gateway and 1 Central servers.
Step 2: Then, we collect and load the data using the Multi-Sensor Medical IoT Dataset.
Step 3: Next, we forward the critical and non-critical sensor data to the central server using conventional scheduling techniques.
Step 4: Finally, we plot and analyze the following performance metrics:
4.1: Number of Sensor nodes vs Latency (ms)
4.2: Number of Sensor nodes vs Throughput (mbps)
4.3: Number of Sensor nodes vs Packet Loss Rate (%)
4.4: Number of Sensor nodes vs Packet Delivery Rate (%)
Scenario 2: (With Network Slicing):
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Step 1: Initially, we constructed a 5G network with 50 Sensor nodes, 2 Gateway and 1 servers.
Step 2: Then, we collect and load the data using the Multi-Sensor Medical IoT Dataset.
Step 3: Next, we dynamically assign traffic to appropriate network slices such as URLLC slices for critical data and mMTC slices for non-critical sensor data using Priority-based scheduling technique and forward traffic data to the central server.
Step 4: Finally, we plot and analyze the following performance metrics:
4.1: Number of Sensor nodes vs Latency (ms)
4.2: Number of Sensor nodes vs Throughput (mbps)
4.3: Number of Sensor nodes vs Packet Loss Rate (%)
4.4: Number of Sensor nodes vs Packet Delivery Rate (%)
Software Requirements:
1. Development Tool: OMNeT++ 4.6 or above
2. Operating System: Windows 10 (64-bit) or above
Dataset:
Link : https://www.kaggle.com/datasets/programmer3/smart-health-iot-sensor-dataset
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.
| 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 |