MAC Protocol For Optimization Of Energy Latency Of WSN Projects

Title:- An Improved Asynchronous MAC Protocol (IA-MAC) For Optimization Of Energy & Latency Of Wireless Sensor Network For Continuous Surveillance Applications Having Infrequent Critical Data

Implementation plan:

Scenario 1 : (Using IA-MAC protocol)

Step 1: Initially We constructed a Wireless Sensor Network (WSN) with 100 sensor nodes(with Wake Up Receiver), 2 Gateways and 1 server.

Step 2: Then, we minimize idle listening, collisions, and optimize energy consumption using Improved Asynchronous MAC (IA-MAC) protocol.

Step 3: Next, we Implement an event-driven wake-up mechanism, allowing sensor nodes to remain in sleep mode until triggered by data transmission requests.

Step 4: Next, we forward the sensor data efficiently using multi-hop communication support.

Step 5: Next, We Develop an adaptive duty cycle mechanism to balance energy efficiency and responsiveness based on network conditions and traffic patterns.

Step 6: Next, we Optimize protocol parameters, such as wake-up sensitivity and transmission scheduling, to minimize false wake-ups and unnecessary energy usage.

Step 7: Finally, we plot performance for the following metrics:

7.1: Number of sensor nodes vs. Average Collision Rate(%)

7.2: Number of sensor nodes vs. Throughput (Mbps)

7.3: Number of sensor nodes vs. Latency (ms)

7.4: Number of sensor nodes vs. Energy Consumption (J)

7.5: Number of sensor nodes vs. Packet delivery ratio (%)

7.6: Number of sensor nodes vs. Network Lifetime(ms)


Scenario 2 : (Using FAWR protocol)


Step 1: Initially We constructed a Wireless Sensor Network (WSN) with 100 sensor nodes(with Wake Up Receiver), 2 Gateways and 1 server.

Step 2: Then, we minimize idle listening, collisions, and optimize energy consumption using Fast Adaptive Wake-up Receiver(FAWR) protocol.

Step 3: Next, we Implement an event-driven wake-up mechanism, allowing sensor nodes to remain in sleep mode until triggered by data transmission requests.

Step 4: Next, we forward the sensor data efficiently using multi-hop communication support.

Step 5: Next, We Develop an adaptive duty cycle mechanism to balance energy efficiency and responsiveness based on network conditions and traffic patterns.

Step 6: Next, we Optimize protocol parameters, such as wake-up sensitivity and transmission scheduling, to minimize false wake-ups and unnecessary energy usage.

Step 7: Finally, we plot performance for the following metrics:

7.1: Number of sensor nodes vs. Average Collision Rate(%)

7.2: Number of sensor nodes vs. Throughput (Mbps)

7.3: Number of sensor nodes vs. Latency (ms)

7.4: Number of sensor nodes vs. Energy Consumption (J)

7.5: Number of sensor nodes vs. Packet delivery ratio (%)

7.6: Number of sensor nodes vs. Network Lifetime(ms)


Scenario 3 : (Using OPWUM protocol)


Step 1: Initially We constructed a Wireless Sensor Network (WSN) with 100 sensor nodes(with Wake Up Receiver), 2 Gateways and 1 server.

Step 2: Then, we minimize idle listening, collisions, and optimize energy consumption using Optimized Predictive Wake-Up Mechanism(OPWUM) protocol.

Step 3: Next, we Implement an event-driven wake-up mechanism, allowing sensor nodes to remain in sleep mode until triggered by data transmission requests.

Step 4: Next, we forward the sensor data efficiently using multi-hop communication support.

Step 5: Next, We Develop an adaptive duty cycle mechanism to balance energy efficiency and responsiveness based on network conditions and traffic patterns.

Step 6: Next, we Optimize protocol parameters, such as wake-up sensitivity and transmission scheduling, to minimize false wake-ups and unnecessary energy usage.

Step 7: Finally, we plot performance for the following metrics:

7.1: Number of sensor nodes vs. Average Collision Rate(%)

7.2: Number of sensor nodes vs. Throughput (Mbps)

7.3: Number of sensor nodes vs. Latency (ms)

7.4: Number of sensor nodes vs. Energy Consumption (J)

7.5: Number of sensor nodes vs. Packet delivery ratio (%)

7.6: Number of sensor nodes vs. Network Lifetime(ms)


Software Requirements:


1. Development Tool: OMNeT++ 4.6 or above with MiXiM framework

2. Operating System: Windows 10 (64-bit) or above



Note:


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.

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