Dynamic Strategy for Adaptive Block Size Optimization in Blockchain Technology

Blockchain technology transforms the ecosystem of the digital world by introducing decentralization, security, and transparency. It plays a vital role in DeFi, healthcare, commerce, industries, education, and supply chain management. However, the scalability factor is a challenge, especially the block size for performance. It affects transaction throughput, computational efficiency, and energy usage, which creates a gap that makes the blockchain system move towards vital solutions. We presented a dynamic framework for optimizing a block size and addressing the optimized solution for the scalability issue. We investigated the Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) algorithms with advanced data structures, Merkle trees, and Directed Acyclic Graphs (DAGs). The proposed framework improves transaction processing while ensuring efficient resource management. The designed framework is helpful for private blockchain transaction networks. It adapts to multiple domains, meeting diverse application requirements. The proposed framework is scalable and effective in homogeneous private blockchain network environments. This study highlights block size as a critical factor in scalability and suggests a strategy to increase private blockchain capacity. It ensures the system can handle growing users and homogeneous network requirements. The findings contribute to making blockchain more scalable, efficient, and sustainable for future green tech ecosystems.