# Comprehensive Review of Storage Optimization Techniques in Blockchain Systems
## 5 Summary and Future Directions
### Summary
#### 5.1.4 Scalability Analysis  
In blockchain networks, optimizing storage technologies is critical for enhancing scalability. These technologies, such as node pruning, IPFS, sharded storage, erasure coding optimization, data deduplication, and data compression, address scalability from various angles. For example, node pruning reduces storage burdens by discarding unnecessary data, while IPFS provides an efficient decentralized storage solution for large files. Sharded storage divides data into smaller, more manageable chunks, which can be distributed across different nodes, facilitating faster access and reducing bottlenecks. Erasure coding ensures data redundancy and fault tolerance while improving data integrity and reducing storage costs without generating excessive copies. Data deduplication saves space by eliminating redundant data, and data compression optimizes the use of available storage resources by reducing the size of stored data. These techniques address scalability challenges in different ways, enabling blockchain networks to effectively scale as data volume increasesand the number of nodes grows. For instance, IPFS is particularly useful for decentralized applications (dApps) that handle large files, while sharded storage effectively meets the demands of high-throughput applications. Erasure coding and data deduplication are especially suitable for systems that prioritize data integrity and efficiency. The scalability performance of each technique depends on its implementation mechanisms and the specific use cases it serves. For example, node pruning is highly effective for private or permissioned blockchains, as it can reduce historical transaction data but may not be suitable for public blockchains that require full transaction visibility. Similarly, data compression can reduce storage costs, but its effectiveness may decrease in environments that require high-frequency updates. By combining these techniques, blockchain networks can optimize storage efficiency and scalability, better managing the growing data volumes and expanding nodes. The key is to select and integrate the most appropriate technologies based on the specific requirements and constraints of the blockchain network. Table 7 below illustrates the performance of these blockchain storage optimization techniques in addressing scalability with respect to both increasing data volumes and the growth of the number of nodes. It provides applicable use cases for each scenario, summarizing how these techniques can improve the efficiency of blockchain systems and offering specific references for different application scenarios. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Technique** & **Impact of Data Volume** & **Impact of Node Count on Scalability** & **Impact on Throughput Scalability** & **Applicable Scenarios** \\ \hline \multirow{4}{*}{Pruning technique} & Pruning historical data & RRedues hardware & \multirow{4}{*}{reducing storage and computation overhead} & \multirow{4}{*}{Lightweight node operation for average users} \\  & significantly reduces storage requirements, but & more users to run nodes, & & \\  & state data still grows with & while full nodes maintain & \multirow{4}{*}{can improve throughput.}