# Towards an Optimized Blockchain-Based Secure Medical Prescription-Management System
## 5 Experimental Results
### Performance Analysis
As a result, the throughput, representing the rate of successful transactions processed, tends to be higher in such scenarios. In contrast, larger networks with a greater number of voters can experience relatively more intricate consensus negotiations, potentially leading to a slightly lower throughput due to the increased coordination efforts required among a larger set of nodes. Finally, notice that, as the send rate increases, the throughput also experiences a corresponding rise. This trend can be linked to the network's capacity to manage a higher influx of transactions, allowing for faster processing and validation. However, beyond a certain threshold specific to each network size, a noteworthy transition occurs. The throughput, after initially rising, reaches a ceiling and becomes relatively constant despite further increases in the send rate. This phenomenon can be explained by the inherent limitations of the network's capacity, resource allocation, and processing capabilities. As the network becomes saturated with a high volume of incoming transactions, it reaches a point where additional transaction submissions do not significantly enhance the overall throughput. Instead, the network operates at its peak processing capacity, and any subsequent increase in the send rate has a limited effect on throughput improvement. Investigating the latency variations, Figure 11 illustrates the results of the studied functions within networks of 5 nodes, 10 nodes, and 20 nodes with various send rates. Actually, these results are correlated with the throughput ones. Indeed, as the size of the blockchain network grows larger, the latency tends to increase. This increase can be attributed to the larger number of nodes and the complexity involved in reaching consensus across a larger distributed network. Furthermore, the latency experiences an upward shift as the send rate increases. This happens because more transactions competing for network resources and processing capacity result in increased latency. Finally, the latency and throughput results of the getPresc() function are reported in Figure 12. Experiments on read-only transactions showed that the process of reading data from the blockchain incurred minimal latency, meaning the time delay between initiating the request and receiving the data was negligible (ranging from 0.01 s to 0.04 s). This is due to the inherent design of blockchain systems, where data retrieval operations primarily involve accessing already stored information from the local data of the node receiving the request, without performing any complex computational tasks. As a result, the time taken to retrieve data during read operations is typically quite low. Moreover, notice that the latency outcomes remain consistently comparable across the networks with 5 nodes, 10 nodes, and 20 nodes. Furthermore, the throughput of the getPresc() function within all the tested blockchain networks exhibits a linear relationship with the number of transactions or requests being processed concurrently (send rate). This means that, as the number of simultaneous read requests increases, the system's capacity to handle these requests scales proportionally. The linear relationship between throughput and concurrent read requests underscores the  
Figure 11: Effect of send rate on latency. decentralized nature of blockchain networks and their ability to efficiently serve multiple pharmacists accessing data in parallel. To summarize, we provide a comparative analysis of our proposed solution for an optimized blockchain-based secure medical prescription management system with existing solutions. A condensed overview of this analysis is provided in Table 4.