## 1 Introduction  
The rapid growth of the Internet of Things (IoT) has notably transformed industries such as healthcare, transportation, and smart cities, enhancing real-time data collection and decision-making processes [1]. By 2030, it is estimated that over 75 billion IoT devices will be connected, underscoring their critical role in the digital ecosystem. However, the widespread adoption of IoT technologies also introduces significant challenges, particularly in identity management, security, and data privacy. Conventional identity management systems operate primarily through a centralized framework, depending on a single authority to authenticate and manage device identities. Although these systems perform adequately in specific cases, they inherently possess vulnerabilities such as single points of failure, restricted scalability, and limited data privacy. These issues become more pronounced in large-scale IoT implementations, where the number of interconnected devices can strain centralized structures, thus increasing the chances of security breaches and system interruptions. To address these challenges, decentralized identity (DID) frameworks have emerged as a robust alternative, aligning with the principles of Web 3.0, which emphasize user autonomy, data sovereignty, and trustless interactions. Blockchain technology, characterized by its immutability, transparency, and distributed architecture, provides a foundation for such systems [2; 3]. However, the high computational costs and scalability issues associated with traditional blockchain platforms, such as Bitcoin and Ethereum, make them suboptimal for resource-constrained IoT environments [4; 5]. The Directed Acyclic Graph (DAG)-based technology, exemplified by the IOTA Tangle, provides a promising alternative to traditional blockchain architectures for distributed ledger systems. Unlike blockchains, the IOTA Tangle uses a graph structure where each transaction validates two or more previous transactions, eliminating the need for miners and enabling feeeless, parallel transactions. This design significantly improves scalability and energy efficiency, making it particularly suitable for Internet of Things (IoT) applications that require lightweight, cost-effective, and high-performance solutions. In the IOTA Tangle, each transaction serves as the smallest unit of consensus, with the Markov Chain Monte Carlo (MCMC) method used to attach new transactions and maintain an equilibrium distribution within the network. Consensus is achieved through transaction validation performed by all nodes, which ensures decentralization, security, and robustness without the need for a traditional Proof-of-Work (PoW) system for mining. Instead, IOTA employs a lightweight PoW mechanism solely to prevent spam and dishonest transactions. Compared to blockchain, the Tangle's asynchronous and parallel processing eliminates bottlenecks caused by block production, reducing delays and enhancing throughput as the network scales. This unique property allows the Tangle to handle increasing transaction loads effectively, with higher network activity leading to faster transaction validation. This scalability is particularly advantageous for IoT ecosystems, where a vast number of low-power devices generate frequent microtransactions. Additionally, the IOTA Tangle provides a robust framework for advanced identity management, supporting concepts such as Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs). These technologies enable secure device authentication and efficient data exchange, making IOTA an attractive solution for managing large-scale IoT networks. Its design addresses challenges in resource-constrained environments while ensuring high levels of security, privacy, and interoperability. Self-Sovereign Identity (SSI) allows individuals and organizations to store their identity data locally, choosing what information to share without relying on centralized identity providers.