Performance Evaluation and Optimization of MAM for Data Marketplace in IoT

This paper presents a secure and verifiable data storage architecture utilizing Masked Authenticated Messaging (MAM) within the IOTA Tangle, aimed at automating the trading of digital assets and services in an IoT ecosystem. MAM operations, such as channel and endpoint creation and data attachment, were evaluated on different hardware platforms, including a PC and Raspberry Pi 3. Results indicate that while MAM operations are computationally feasible on higher-powered machines, they become significantly time-consuming on lower-powered devices, such as the Raspberry Pi 3, especially as the Merkle Signature Scheme (MSS) height increases. The performance of MAM on low-level IoT devices poses challenges due to limited computational power and unstable internet connections. To address these issues, the paper proposes offloading MAM operations to brokers equipped with powerful machines and enhanced processing capabilities using Tangle-accelerator and Ethereum clients. This approach aims to lower the threshold for IoT device participation while ensuring data privacy and operational efficiency. The findings highlight the importance of improving MAM performance to make it a viable solution for data marketplaces in IoT environments.