Comparing blockchain and DAG technologies for smart agriculture traceability in terms of efficiency and latency

Abstract

Distributed Ledger Technologies (DLT), such as Bitcoin, Ethereum, and Directed Acyclic Graphs (DAG), are being positioned as a promising solution for smart agriculture by enabling secure, decentralized, and transparent traceability systems. However, these technologies face challenges related to scalability, latency, and efficiency in IoT environments. In this study, we conduct a comparative analysis of Bitcoin, Ethereum, and DAG technologies through extensive simulations, varying transaction generation rates and network latencies. A key methodological innovation of this research is the detailed codification of agricultural data transactions, encompassing parameters such as crop type, fertilization, harvesting, and transportation, enabling a structured and scalable approach to data representation. Our results reveal that Bitcoin's robustness is hindered by its high sensitivity to latency and network load, with inclusion times exceeding 700 s. Ethereum demonstrates better adaptability, with controlled inclusion times ranging from 12.91 to 35.76 s under varying conditions. DAG outperforms both, achieving significantly lower inclusion times between 4.27 and 22.25 s, highlighting its suitability for real-time applications. To the best of our knowledge, this is the first study to provide a direct comparison of these technologies in the context of agricultural traceability, showcasing the advantages and limitations of DAG-based systems for managing and scaling agricultural IoT networks.