# Blockchain-Based E-Voting Mechanisms: A Survey and a Proposal +
## 6 Implementation
### Experimental Analysis and Observations  
The experimental analysis of our blockchain-based electronic voting system focused on evaluating its performance, scalability, power efficiency, and security. The voting processwas simulated with 10,000 randomly generated votes for three candidates to assess the system's ability to handle substantial voting data. We employed the multiprocessing capabilities of the Raspberry Pi to concurrently execute the Borda count and Condorcet method algorithms, demonstrating the system's efficiency in processing votes. The concurrent execution ensured optimal utilization of the multi-core processor, with processing time scaling proportionally to the number of votes. The novel branching blockchain structure proves to be highly scalable, maintaining consistent performance even with increased voting loads. Each branchchain operated independently, allowing simultaneous processing of the different voting methodologies. Smart markers ensure precise and rapid results while preserving data integrity. The measured power consumption shows that our system is suitable for all environments and is available for use in resource-constrained environments as well. Security and data integrity were paramount in our design. Though any consensus method will work with our methodology, we employed Practical Byzantine Fault Tolerance (PBFT) protocol, ensuring robustness against faulty nodes and maintaining the integrity of the voting results. Each block's cryptographic hash linked to its predecessor creates a tamper-proof ledger. The branching structure allows verification of each branchchain independently, enhancing election fairness and preventing biases. In cases where the Condorcet method resulted in a tie, the Borda count served as a secondary check, ensuring a decisive outcome. In Table 3, we list the average time to append the blocks to their branchchains. In Table 4, we list the maximum power consumption in Watts viewed on the power meter plug. Our findings indicate that the computational demands for hash calculations and execution of the voting algorithms are relatively modest. The multiprocessing module is efficiently used in the Raspberry Pi 3's multi-core processor and we expect enhanced performance on more robust hardware. Analyzing the data presented in Table 3, it can be seen that the time required for mining two blocks concurrently in the system scales proportionally with the increase in votes per block. The overall time includes the branching of the blockchain and simultaneous execution of the Borda count and Condorcet method, and culminates in the generation of two new blocks, representing the collective voting data and final results for each branchchain in the Borda-Condorcet chain. The scalability of the system, as demonstrated by these results, indicates its effective functionality even in resource-constrained contexts. Table 4 shows the system's power efficiency, with the highest power consumption recorded as 4.8 Watts, from the base power consumption of 2.5 Watts, even at the upper limit of 200,000 votes per block. This efficiency in power usage further confirms the suitability of our system for use in limited-resource environments. \begin{table}
\begin{tabular}{c c} \hline \hline
**Votes per Block** & **Power Consumption per Block (Watt)** \\ \hline
100 & 4.4 \\
1000 & 4.1 \\
10,000 & 4.1 \\
100,000 & 4.7 \\
200,000 & 4.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Highest power consumed when mining two blocks in tandem (one per branchchain). \begin{table}
\begin{tabular}{c c} \hline \hline
**Votes per Block** & **Time per Block (s)** \\ \hline
100 & 0.02184 \\
1000 & 0.06666 \\
10,000 & 0.5661 \\
100,000 & 6.39104 \\
200,000 & 12.99719 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Time required to mine two blocks in tandem (one per branchchain). These results show that our blockchain-based e-voting system is not only compatible but also optimally designed for deployment in resource-constrained environments, such as sensor networks.