# Efficient and Secure Management of Medical Data Sharing Based on Blockchain Technology
## 5 Experiments
### Experimental Results and Analysis  
#### 5.3.1 Data Upload and Query Experiment  
In order to test the performance of the blockchain network that we built, we conducted data upload and query experiments. We tested the impact of the number of organizations on network performance by changing the number of organizations in the blockchain network. In the experiment, we selected caliper as the testing tool and performed performance tests on networks containing 3-7 organizations. In caliper, we set up 10 workers to complete 100,000 random uploads and queries of medical and operational behaviors data. We used metrics such as Send Rates, Maximum Latency, Min Latency, Avg Latency, and Throughput to measure the performance of the medical data management platform. The results after five tests and their average are shown in Tables A1-A5. For uploading medical data, when the number of organizations is 3, the send rate is 1361.7 TPS (transaction per second) and the throughput is 1349.3 TPS. However, as the number of organizations increases to 7, the send rate decreases to 794.7 TPS and the throughput drops to 782.8 TPS. Simultaneously, the maximum latency increases from 2.05 s to 2.28 s, and the average latency increases from 0.11 s to 0.37 s. Similar results are observed for uploading operational behaviors data, where the send rate decreases from 1256.3 TPS to 789.9 TPS, the throughput decreases from 1247.1 TPS to 778.6 TPS, the maximum latency increases from 2.03 s to 2.04 s, and the average latency increases from 0.10 s to 0.37 s.  
When querying medical data, the increase in the number of organizations leads to a decrease in the send rate from 1645.3 TPS to 1192.4 TPS and in throughput from 1603.2 TPS to 1179.9 TPS. The maximum latency increases from 1.95 s to 2.01 s, and the average latency increases from 0.09 s to 0.26 s. Similar results are observed for querying operational behaviors data, where the send rate decreases from 1640.8 TPS to 1184.7 TPS, throughput decreases from 1599.8 TPS to 1173.8 TPS, maximum latency increases from 1.92 s to 2.08 s, and average latency increases from 0.09 s to 0.27 s.  
In the upload and query experiments, the core metric is throughput. To facilitate observing the relationship between throughput and the number of organizations, we use Figure 8 to display the throughput values in Tables A1-A5. From Figure 8, we can observe that as the number of organizations increases, both upload and query throughput tend to decrease. This is because as the number of organizations increases, the cost of consensus and communication between organizations rises, requiring more resources, leading to a decrease in throughput. In the platform, queries are also considered as transactions, which leads to a smaller difference in throughput between queries and uploads. However, in all experiments, the throughput value of queries is higher than uploads. We speculate that when the platform processes query transactions, the overhead of writing query transactions is lower than that of writing medical or operational behaviors data. The throughput of uploading medical data is slightly higher than that of operational behaviors data, because the size of individual operational behaviors data is slightly larger than that of medical data, leading to more time spent on writing operational behaviors data and a subsequent decrease in throughput. In the tests of querying operational behaviors and medical data, their throughputs are quite close. This is because the time spent on reading and obtaining data in nodes is negligible compared to the time for consensus among nodes for query transactions, and ultimately the throughput rate of query depends on the efficiency of reaching consensus among nodes in the platform. By testing the throughput of uploading and querying data in different numbers of organizations, and considering the actual business requirements of medical data management, the platform we have built can meet the needs of data uploading and querying. Next, we describe a test of the provenance performance of the platform.