## 5 Performance Evaluation
### Simulation Setup  
To evaluate the performance of the proposed methods, we utilized Castalia, an OMNeT++-based simulator written in C++. Castalia is well-suited for WSN simulations, as it incorporates real-world environmental parameters, including carrier sensing, collision handling, individual MAC modules, routing modules, and radio modules. For our simulations, we configured the CC2420 radio module, a built-in parameter setup available in Castalia, to ensure accurate wireless communication modeling.  
Since the experiments were conducted in a simulation environment rather than on a real-time testbed, we employed the event-triggered traffic application system named \"ThroughputTest\", available in Castalia. In this setup, a randomly selected node generates data packets at specified intervals following a given packet rate. All sensor nodes in the network communicated using the BoX-MAC protocol with duty cycles to conserve energy. Because of its native support in the Castalia simulator and compatibility with asynchronous low-duty-cycle WSNs, BoX-MAC was chosen. It is perfect for comparing lightweight routing protocols like FCM-OR because of its low control overhead and energy-efficient wake-up policy. However, our routing layer improvements recognize and less its limited scalability and dependence on ACKs. Our proposed method, FCM-OR, wasimplemented on this MAC protocol alongside two widely used OR protocols, ORW and ORR, to compare their performance, primarily in terms of energy consumption.  
Initially, we deployed 100 to 1000 sensor nodes non-uniformly in a 500 m \(\times\) 500 m area and placed a sink node at the top-right corner of the sensor field. Except for the sink node, all nodes used a duty cycle ranging from 0.2 to 0.9, and each time frame was fixed at 610 ms. Hence, every 610 ms, the radio of a node changed its state at least once. Each node had a transmission range of 50 m and a carrier sensing range of 100 m. This estimated the minimum hop distance from any corner of the field by approximately 10, and in the worst case, the hop distance could be increased by up to 15. To ensure uneven randomness of the node deployment, we first assumed the sensor field to be a grid and then placed the nodes using a random distribution on discontinuous grid boxes. We increased the distribution number of random deployments on the grid boxes to increase the degree of uneven density of the nodes.  
At the start of the simulation, the nodes began their individual duty cycles and waited for a beacon signal [3; 53] from their one-hop distance-apart neighbor (nearer to the sink). The sink initiated this process. With this beacon signal, the nodes sent their FR values and information about themselves, which were required to calculate the FR. Unlike ORW and ORR, in the proposed protocol, the received radio signal strength for a node was used as the link quality value for that node. Accordingly, we could save energy that would be spent on the probing method for link quality estimation of a node [3]. We optimized the routing metric equations of ORW and ORR by adding FCM logic for the forwarder node selection (see Equations (5) and (6)).