# Research on Blockchain Data Availability and Storage Scalability
## 5 Model Validation
### The Impact of Node Type on Data Availability  
We constructed SSF and randomly requested block data with lengths of 10, 100, 1000, and 10,000 from full nodes, resulting in an average response time as shown in Figure 3.  
As depicted in Figure 3, in the simulated blockchain network, a full node could obtain target data within 0.31 s irrespective of the number of target blocks acquired. The actual time limit \(t\) was set much higher than the duration required for full nodes to obtain data locally. Thus, full nodes had a 100% probability of acquiring data locally within the time limit.  
We built SSFL and SSFE with the proportion of SPV nodes and ESPV nodes set at 10% each. The SPV node requested block data with a length of 1000 from full nodes, while the ESPV node verified the block data with a length of 1000. Figure 4 depicts the change in data availability.  
Figure 3: Average response time of different block lengths.  
The experimental results indicate that in SSFL, during the initial stage, SPV nodes send data requests to full nodes, which process the requests and retrieve the data. During this phase, the data availability is 0. However, with time, SPV nodes gradually receive data from the full nodes, leading to a steady increase in data availability and ultimately reaching 100%. In SSFE, the simulation system completes most of the verification work within 0.3 s, after which the data availability slowly improves, eventually reaching 100% at 0.5 s.  
According to the experimental results in Figure 4, the time limits \(t\) in SSFL and SSFE were set to 0.8 s and 0.5 s respectively. If any data received by the node exceeded the time limit, it was deemed unavailable. The proportion of SPV nodes and ESPV nodes was continuously changed, and the changes in data availability are summarized in Figure 5.  
The experimental results indicate that in SSFL, when the proportion of SPV nodes is relatively low, the data availability level is higher. However, as the proportion of SPV nodes increases, data availability sharply declines. This is because a large number of data requests flow to full nodes, causing more requests to be processed and increasing the data response time. The response time for a large amount of data exceeds the time limit, rendering it unavailable and thus leading to a decrease in the data availability level. Conversely, in SSFE, even though the proportion of ESPV nodes continues to increase, data availability remains high.  
Figure 4: Data availability changes.  
Figure 5: Data availability under different ratios of degraded nodes. (**a**) SSFL; (**b**) SSFE.  
The times taken for the system to achieve 100% data availability under different proportions of degraded nodes are shown in Figure 6.  
The experimental results demonstrate that in SSFL, as the proportion of SPV nodes increases, the time taken to achieve 100% data availability significantly increases. An excessive number of SPV nodes means that a full node needs to handle a greater number of requests, greatly prolonging data response time and leading to an increasingly longer time to achieve 100% data availability. Conversely, in SSFE, as the proportion of ESPV nodes increases, the trend of the increase in time to reach 100% data availability is relatively mild. A full node does not need to handle too many requests from ESPV nodes, and the data response time is not significantly prolonged.  
From the above experimental results, it can be concluded that node types have an impact on the data availability of blockchain within a time limit. If there are multiple node types, the proportion of their numbers can also affect data availability.