# Integrating Blockchains with the IoT: A Review of Architectures and Marine Use Cases
## 3 BioT Architectures and Communication
### BioT Implementation Choices  
One of the primary obstacles posed to the integration of blockchain technology with the IoT has to do with successfully managing the balance between the blockchain's computational and storage demands and the limited processing capabilities of most IoT devices [4; 30; 44]. In this respect, addressing this issue requires the meticulous consideration of several architectural designs that can optimize system performance without overwhelming the devices. This section, therefore, elaborates on different architectural strategies, such as offloading intensive tasks to edge nodes or utilizing lightweight blockchain protocols, which have been specifically developed to tackle this challenge effectively. A leading architectural decision involves selecting the type of node to be deployed on IoT devices. More specifically, full nodes offer higher levels of security by storing a complete copy of the blockchain. However, these nodes require significant computational resources, which makes them impractical for most IoT setups. Moreover, IoT hardware is typically resource-constrained, which makes it unsuitable for supporting real-time transaction processing. As a result, the additional storage and computational power required for running a full node can further increase the resource burden on these devices [30]. It should be noted that full nodes can often be deployed on edge or cloud servers, as these systems have the necessary computational resources and storage capacity to manage the entire blockchain [43]. An alternative lies in lightweight client architectures, which enable devices to rely on full nodes for data validation while storing minimal blockchain data. Nevertheless, although this approach manages to reduce resource requirements, it introduces a dependency on full nodes as well [30; 43]. To address this concern, [PERSON] and [PERSON] [3] suggest that the future of successful blockchain integration in the IoT depends on the development of lightweight blockchain architectures that adopt alternative consensus mechanisms rather than resource-intensive ones such as PoW. Another critical aspect of designing a BIoT architecture is determining where data should be processed and stored. Although traditional cloud-based architectures can be very efficient for data aggregation and protocol conversion, they face significant challenges in terms of scalability and reliability [30]. In many respects, centralized cloud solutions can introduce a single point of failure [3]. If the server is compromised, this can disrupt operations and expose sensitive information. Additionally, the remote nature of cloud data centers often leads to latency and bandwidth issues, affecting the overall performance. As IoT deployments expand, research has shown that cloud-based models find it increasingly challenging to manage larger scales while remaining reliable and efficient [30]. To address these limitations, edge computing provides a compelling solution by processing data closer to their source, thereby reducing network traffic and latency. One way to implement edge computing is through \"Cloudlets\", which act as mini-clouds at the edge. They are utilized to provide fast responses for compute-intensive tasks that traditional gateways may struggle with due to resource constraints and are often employed in scenarios where low latency and high computing power are needed [3]. However, provisioning IoT services on edge devices can be challenging in terms of design and maintenance. One way to address this is by using virtual IoT resources, which allow for the deployment of small, manageable services across multiple devices or hosts [45]. An example of leveraging edge computing for IoT management is \"EdgeChain\", proposed by [PERSON] et al. [46], which integrates blockchains and smart contracts to manage IoT devices by linking them to edge cloud resources.