In recent years, Distributed Ledger Technologies (DLTs) have emerged as ground-breaking innovations, capturing attention across diverse sectors. Functioning as encrypted, shared databases, DLTs enable each participant, or peer, to operate independently within a decentralized network. This architecture provides a secure, unalterable platform for data exchange among users or devices, fostering applications in healthcare, energy, finance, and more. However, traditional Blockchain technology, despite its successes, faces limitations in scalability and energy efficiency, particularly in areas like the Internet of Things (IoTs), the sharing economy, and smart cities. This thesis investigates Directed Acyclic Graph (DAG)-based DLTs, with a focus on the IOTA Tangle, which allows transactions to reference one another in a non-linear, parallel manner, eliminating the need for miners and thereby reducing transaction fees. This makes DAG-based DLTs potentially more suited for IoT and smart city applications, considering their scalability and economic advantages.

This thesis investigates the network layer design of DAG-based distributed ledgers and their multifaceted applications. It begins with a foundational overview of DLTs and key aspects of DAG-based network layers, including an introduction to the IOTA Tangle. The study then evaluates a novel access control protocol for DAG-based DLTs, proposing enhancements to strengthen security against vulnerabilities and various attack scenarios. An algorithm to regulate block addition in DAG networks is presented, crucial for ensuring block validity, managing the tip pool size, and upholding ledger consistency. The thesis also introduces a unique user-node interaction model for DAG environments, aimed at optimizing traffic distribution across nodes to enhance service quality for users. It further explores DLT's role in facilitating social contracts and influencing agent behavior in smart city contexts. Demonstrating a practical application, the thesis unveils a prototype of a wearable smart mask, designed to encourage mask-wearing through incentive mechanisms, illustrating the potential of DAG-based DLTs in real-world scenarios.