# Comprehensive Review of Storage Optimization Techniques in Blockchain Systems
## 4 Methods
### Pruning Technique
As the blockchain expands, older blocks can be safely pruned, retaining only the latest snapshot and accumulator state to track and verify the current transaction state. By reducing the storage of historical data and optimizing the verification process, the securePrune protocol effectively mitigates the issue of storage redundancy within blockchain systems. Runing techniques have been applied to the Internet of Things (IoT) industry. [PERSON] et al. [PERSON] et al. (2018) proposed an optimized blockchain architecture to address large-scale network storage challenges. IoT devices generate massive amounts of transaction data, continuously increasing storage demands. To address this issue, MOF-BC (Memory Optimized and Flexible Blockchain) introduces a memory-optimized and flexible blockchain solution, allowing users and service providers to reduce storage redundancy and manage stored data more flexibly through deletion and transaction summarization. Users can delete transactions no longer needed or consolidate multiple transactions into a summary to minimize storage space. Additionally, MOF-BC offers memory optimization modes, including a temporary  
Figure 5: Disk space reclaiming process. mode (where transactions are automatically deleted after a set time), a permanent mode (where transactions are stored permanently), and a summarizable mode (where transactions can be merged), providing users with diverse storage options. Experimental results indicate that MOF-BC can reduce blockchain storage consumption by up to 25%, significantly improving storage efficiency and lowering long-term storage costs, thus enhancing the practicality of blockchain in the IoT industry. In the scheme proposed by [PERSON] et al. [66], the authors challenge the prevailing belief that node operators in blockchain networks cannot delete local data. Blockchain is generally regarded as immutable, meaning that once data are published, they cannot be deleted or modified. However, for legal and ethical reasons, certain node operators may be required to delete locally stored data such as potentially illegal content, privacy-sensitive information, or other inappropriate data. The authors introduce a solution termed Functionality-Preserving Local Erasure (FPLE). By allowing blockchain nodes to selectively delete unnecessary data, FPLE significantly reduces blockchain data storage demands. FPLE enables node operators to delete specific data (such as transaction outputs) from local storage in accordance with specific legal or ethical requirements without altering the blockchain protocol, thus avoiding the storage of data that may pose legal risks or conflict with individual values. Despite deleting some data, the FPLE scheme retains the core functionality of nodes, allowing them to continue participating effectively in network consensus and transaction validation. For future verification processes that may rely on deleted data, FPLE leverages Simplified Payment Verification (SPV), enabling nodes to validate without storing a complete transaction history. This not only reduces storage redundancy but also preserves the decentralization and robustness of the blockchain network. [PERSON] et al. [67] proposed a Swarm-based Pruning technique as a solution for optimizing blockchain storage efficiency through intelligent algorithms. This approach specifically addresses the storage and synchronization challenges arising from the continuous growth of data in blockchain systems. To solve these issues, Swarm-based Pruning introduces a selective pruning method based on data usage, which deletes only outdated data that are no longer needed, including spent transaction records or previous versions of smart contracts. This approach significantly reduces data storage demands without compromising the overall security and consistency of the blockchain. The core of Swarm-based Pruning is the use of the Particle Swarm Optimization (PSO) algorithm.