Experimental Evaluation of Smart Contract Gas Optimization Techniques: A Case Study of a Blockchain-Based Reporting Application System

Abstract

Blockchain-based applications often face scalability challenges due to high gas costs associated with on-chain storage in the Ethereum network, particularly for systems requiring continuous audit logging. This study evaluates smart contract optimization strategies to reduce gas consumption in a blockchain-based mobile reporting system for sexual violence cases. An experimental approach was conducted by implementing four Solidity smart contract models—Baseline, Merkle Tree Aggregation, Storage Optimized (Packed Struct and Enum Encoding), and Conditional Commit—and testing them under scenarios of 50, 100, 500, and 1000 transactions using identical datasets. Gas consumption, transaction cost, latency, and execution time were analyzed using descriptive statistics and non-parametric tests. The results show that the baseline approach produced the highest gas consumption (770,899,033 gas for 1,000 reports), while Storage Optimization reduced it to 177,566,016 gas and Merkle Tree Aggregation to 20,492,732 gas. The Conditional Commit method achieved the lowest gas consumption at 4,308,404 gas with an execution time of 1.08 seconds compared to 143.72 seconds in the baseline. Statistical tests confirmed significant differences among methods (Kruskal–Wallis H = 166.93, p < 0.01; Mann–Whitney p < 0.01), demonstrating that reducing on-chain transactions substantially improves gas efficiency and scalability.