## 3 Research Methodology
### Evaluation Metrics
This metric enables the assessment of the energy consumption of individual frames, providing insights into the energy efficiency of the encryption process at a granular level. The diagram illustrated in Figure 2b showcases a circuit schematic that has been specifically designed for the purpose of measuring power and calculating energy. Power is supplied to the Raspberry Pi board by an Arduino UNO through GPIO pin-4 (5V) and pin-6 (ground). The power line connection between the Arduino and the Raspberry Pi incorporates the INA219 sensor from Texas Instruments [22], which accurately monitors power consumption in real time, and Arduino facilitates the computation and logging of energy consumption. Furthermore, one-way serial communication is established by connecting GPIO pin-14 on the Raspberry Pi to pin-0 on the Arduino. This communication channel serves to initiate and terminate measurements related to power and energy consumption. At the beginning of the encryption process, the Raspberry Pi sends the name of the cipher through the serial communication channel to signal the Arduino to activate the INA219 to start recording power consumption. After the encryption process is completed, another message is sent to the Arduino to signal the termination of power and energy consumption measurement for that specific LWSC. In order to accurately calculate the energy consumption of a specific LWSC while excluding the influence of background processes, the power consumption of the Raspberry Pi is first measured during an initialization phase where only background processes are active. This average power consumption is then subtracted from the current readings while the cipher is executed at discreet time intervals, isolating the power utilized exclusively by that specific LWSC. Figure 2: Connection setup between a Raspberry Pi and an Arduino UNO for power and energy measurement using an INA219 module. Rank provides a unified metric for software performance by balancing performance and resource consumption in lightweight cryptographic ciphers. The term was initially introduced by [PERSON] et al. [PERSON] et al. (2018) and refers to the ratio between the speed at which data are processed and the amount of memory, including both volatile and non-volatile memory, utilized during the encryption process, as illustrated in Equation (1). However, in the context of this research study, we utilized a modified version of Rank, denoted as E-Rank, which incorporates insights from the Figure of Merit (FoM). The FoM was introduced by [PERSON] et al. [PERSON] et al. (2018) to evaluate their LWBC ARMADILLO, and it typically assesses hardware performance, but the equation does not account for power dissipation, as indicated in Equation (2). The authors clarify the exclusion of power dissipation by explaining the direct relationship between dynamic power and total switched capacitance. In hardware implementation of cryptographic ciphers, power is directly linked to the number of gates, as each transistor within a gate contributes to the overall capacitance. When the number of gates increases in a circuit, the total switched capacitance also increases proportionally. The calculation of the Rank metric depends on total memory consumption, which does not have a direct correlation with switched capacitance. Therefore, the incorporation of energy measurement into the Rank provides a more refined evaluation metric for overall software performance. This refined metric is called E-Rank and is presented in Equation (3). During the calculation of E-Rank, applying unit normalization ensures the consistent expression of all metrics in bytes. \[\text{Rank}=\frac{\text{Throughput}}{\text{ROM}+2\times\text{RAM}} \tag{1}\]  
\[\text{FoM}=\frac{\text{Throughput}}{\text{Clock freq}\times\text{Gate count}^{2}} \tag{2}\]  
\[\text{E-Rank}=\frac{\text{Throughput}}{(\text{ROM}+2\times\text{RAM})\times \text{Energy consumption}} \tag{3}\]