## 4 Results: Proof of Concept
### Identity Management Implementation
#### 4.1.3 Verifiable Presentations (VPs)
Lastly, the operating system (Linux-based) running on Raspberry Pi may also have a higher overhead for managing multiple processes compared to the more efficient memory management mechanisms found on more powerful systems such as the Intel Core i5. This further contributes to higher memory consumption when running the same application or algorithm, despite the differences in processor capability. As a result, when using the same approach and algorithms, the lower hardware specifications of Raspberry Pi lead to less efficient use of available resources, resulting in higher memory consumption, slower processing, and higher latency. #### 4.3.3 Node Management

There are two main types of nodes in the IOTA network: full nodes and \"permanodes\". Full nodes can be deployed locally and allow users to store multiple transactions in their

Figure 5: Performance Comparison during execution: Intel Core i5-7500 vs. Raspberry Pi 4.

local database. These nodes can be configured with different storage capacities, with minimal requirements for maintaining ledger consistency. However, when the storage capacity of a full node reaches its limit, the system begins to delete the earliest stored transactions to free up space, potentially resulting in the loss of critical data such as the DID document. Permanodes, on the other hand, are clusters designed to store the complete transaction history of a full node. While IOTA recommends using Scylla to overcome the storage limitations of permanodes, this solution can be prohibitively expensive for many users, depending on the cost of maintaining the node. To address this issue, IOTA is developing a selective permanode solution that would allow users to store only the transactions associated with DID document operations. This selective storage method would significantly reduce costs while ensuring the persistence of critical identity data. Ongoing work on this solution aims to balance the need for long-term data storage with the economic feasibility of operating a node, thus providing a more sustainable approach to decentralized identity management. This work has demonstrated a proof of concept for using the IOTA Tangle in distributed identity management, specifically in IoT scenarios, using the Raspberry Pi 4 as the primary experimental platform. While the results demonstrate the feasibility of the approach, further investigation is required to assess its scalability and applicability to IoT devices with different hardware constraints, such as ESP32 or ARM Cortex-based platforms. Future studies will investigate the performance of the system on these devices to better understand its adaptability to low-power and resource-constrained environments. In addition, mitigation strategies for cryptographic overhead, such as lightweight cryptography and hardware acceleration, will be explored to optimize system efficiency. Large-scale simulations and experiments involving thousands of devices will be conducted to evaluate the scalability of the system and to identify and address potential bottlenecks, thereby laying the groundwork for more comprehensive implementations. Building on the scalability concern, future work will include stress and peak testing to evaluate system performance under high transaction loads and simultaneous communication from multiple IoT devices. These tests will evaluate the system's ability to handle large-scale interactions, with a particular focus on key metrics such as transaction efficiency, latency, and energy consumption. Moreover, a comparative analysis with blockchain-based alternatives will be conducted to provide a clearer perspective on the strengths and limitations of IOTA's Tangle. This includes a detailed evaluation of the dependency on network size and the influence of the IOTA ecosystem on system performance. By quantifying these limitations and comparing them to blockchain solutions, we aim to provide empirical evidence to validate the scalability and robustness of the proposed approach.