Resource Analysis in Blockchain Transactions: An Opcode-Driven Multilayer Graph Approach

Abstract

Blockchain technology has experienced significant growth across various industries. However, challenges such as scalability, high transaction fees, and resource inefficiencies continue to limit its full potential. This paper presents a novel approach using a multilayer graph to model and analyze blockchain transactions, with a focus on resource consumption—specifically opcode execution and gas usage. By categorizing accounts into distinct layers—Externally Owned Accounts (EOAs), smart contracts, oracles, and cross-chain bridges—the graph-based model captures interactions across these account types. Through transaction trace analysis, we extract opcode usage and gas consumption, applying graph-theoretical metrics such as node scoring and edge weighting to identify critical nodes and resource-intensive transactions. Our findings provide new insights into resource-heavy behaviors, revealing optimization opportunities to reduce transaction costs and improve scalability. Additionally, the approach aids in anomaly detection and smart contract optimization, enhancing the cost-effectiveness and performance of blockchain systems.