# Integrating Blockchains with the IoT: A Review of Architectures and Marine Use Cases
## 2 Architectural Foundations of IoT, Blockchains, and MIoT/IoUT
### Architectures and Implementation of MIoT/IoUT Systems
An example of such a protocol is E-CARP, proposed by [PERSON] et al. [42], which enhances both communication and energy efficiency in Underwater Wireless Sensor Networks. The \"Network\" layer handles the two-way transmission of data packets between endpoints and translates protocols, emphasizing efficient data routing to ensure effective communication between routers [16]. This layer is crucial for translating protocols and maintaining the integrity of data as they move between the \"Perception\" and \"Application\" layers. In IoUT systems, the \"Network\" layer's design is particularly complex due to the harsh underwater environment, which necessitates specialized routing protocols and reliable data transmission methods [25]. The \"Data Link\" layer enables underwater sensors to connect with surface stations by managing data exchanges, converting data frames, and coordinating transmission through various communication technologies (e.g., acoustic, optical). Effective channel modeling is essential in this layer, where different channel models are applied to optimize communication in the underwater environment. Models that can account for the unique conditions of each underwater environment (e.g., varying sound speed) are essential for accurately predicting system performance and strategically placing nodes to optimize communication [37]. Figure 4: MIoT TCP/IP architecture. Finally, the \"Physical\" layer's behavior varies depending on the propagation nodes and the types of channels used in each scenario. This layer deals with the physical aspects of data transmission, including signal attenuation, which varies across electromagnetic, acoustic, and optical media. A suitable channel model is necessary for predicting system performance, optimizing node placement, and minimizing the overall power consumption before deployment. The \"Physical\" layer's effective design directly impacts the reliability and efficiency of the entire IoUT system [37]. Building on this foundational understanding, the IoUT system itself is organized into multiple tiers of sensing and communication devices, generally referred to as endpoint nodes, mid-layer nodes, and sink nodes. More specifically, endpoint nodes include sensors, cameras, actuators, and other devices, while mid-layer nodes consist of modems, gateways, and repeaters. Sink nodes are positioned on buoys, ships, satellites, or shore-based stations, forming the higher level components of the IoUT architecture [17]. With respect to implementing IoUT systems, ref. [16] outline three crucial sequential processes: the dynamic perception of the underwater environment, the real-time transmission of data, and intelligent data processing. These processes closely align with the functionality-based architecture discussed by both the aforementioned authors and [PERSON] et al. [37], which highlights how effectively these steps integrate into the framework. Examining this architecture, which is comparatively less complex than the TCP/IP model, provides clarity on the core functions of the IoUT. As revealed by [PERSON] and [PERSON] [16], the first process involves the dynamic and continuous perception of the underwater environment. This step is directly supported by the \"Perception\" layer in the functionality-based architecture, which is responsible for gathering diverse data regarding water properties, quality, aquatic life, and underwater objects. By deploying underwater sensing nodes, GPS sensors, and surface links, the \"Perception\" layer ensures that the necessary data are collected continuously, forming the foundation for real-time monitoring. Another factor that is particularly important when it comes to the effectiveness of data gathering and transmission within an IoUT network is the choice of communication channels (e.g., magnetic induction, optical, acoustic, RF, or hybrid).