# Integrating Blockchains with the IoT: A Review of Architectures and Marine Use Cases
## 3 BioT Architectures and Communication
### BIoT Interaction Models and Traffic Considerations  
An extensive thesis on the issue of communication paradigms is provided by [PERSON] et al. (2018), who present three distinct paradigms for IoT systems, outlining the strengths and limitations of each. Firstly, in the \"direct communication\" model, IoT devices communicate with one another directly without relying on intermediaries or blockchain technology. This method enables the rapid transmission of data by bypassing complex processing. Nevertheless, this model has vulnerabilities in terms of security and privacy, as it lacks the necessary mechanisms to ensure data integrity as well as protection against unauthorized access. On the other hand, the \"blockchain-based communication\" model relies on blockchain technology to route all transactions, creating \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Architecture** & **Description** & **Advantages** & **Disadvantages** \\ \hline \multirow{3}{*}{Cloud computing} & Centralized & \multirow{3}{*}{Scalable processing, centralized control, ease of management} & Higher latency, single points of failure, dependent on internet connectivity \\ \cline{3-4}  & & & \\ \hline \multirow{3}{*}{Edge computing} & Data processing & Low latency, reduced bandwidth, improved devices to reduce latency & Limited processing power, security risks \\ \cline{3-4}  & Distributes & & \\ \cline{3-4}  & Processing between cloud and edge devices using local gateways & Improved scalability, network resilience, enhanced local data management & Increased system complexity, higher deployment costs, coordination challenges \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of cloud, edge, and fog computing approaches. a more reliable system. Although this model may slow down transactions due to the validation process, it provides a structured approach for IoT applications where data integrity and transaction transparency are key priorities. Finally, \"Fog or cloud-based communication\" models leverage fog computing in order to offload computational tasks from IoT devices to fog nodes. In the context of the BIoT, this approach allows nodes to handle the intensive processing required by blockchain algorithms, supporting more efficient communication between IoT devices. By distributing the computational and storage demands away from individual devices, it offers a practical solution for implementing BIoT systems. These communication paradigms and their respective advantages are summarized in Table 3, providing a clear comparison of the models outlined. As discussed previously, integrating blockchains with the IoT aims to decentralize the expanding IoT ecosystem, thus enhancing its overall sustainability and integrity. [PERSON] and [PERSON] (2014, as cited in [8]) proposed this decentralized approach to addressing privacy and trust issues through a \"security through transparency\" model. Traditional centralized models require significant maintenance and improvement costs, which blockchains can mitigate by using a scalable peer-to-peer network. Blockchain networks enable IoT devices to verify and distribute data, such as software updates, through direct, decentralized interactions. This reduces reliance on central servers and allows IoT systems to operate with greater independence. Moreover, in their research, [PERSON] et al. [43] have outlined interaction models between IoT devices and a blockchain network. They identify three primary interaction types:  
1. Direct interaction between the IoT and blockchain: IoT devices access blockchain data saved on edge servers. 2. Direct interaction between IoT nodes: Nodes exchange partial blockchain data via device-to-device links. 3. A hybrid interaction of cloud and edge servers with IoT devices: Devices interact with blockchain data through edge or cloud servers. However, most IoT devices remain lightweight nodes due to limited storage. Figure 6 below provides further clarity on these models, illustrating their key components and interactions.