## 2 Related Work
### Hyperconvergence  
The hyperconverged infrastructure offers several approaches for its implementation. In this subsection, the approaches related to hyperconvergence architectures will be presented, with a focus on storage management. This focus is justified by the central role of storage in the development of hyperconvergence [32] and by the foundation of the architecture proposed in this work, which is based on hyperconvergence approaches for storage. According to [PERSON] et al. (2017) [33], there are various approaches to implementing storage in hyperconverged environments. However, two architectures predominate: those based on VSAs (Virtual Storage Appliances) and storage virtualization integrated directly into the hypervisor. In the VSA architecture, the hypervisor delegates disk control to the VSA, which, in practice, is a virtual machine responsible for consuming storage resources and managing access to these resources by other VMs. The VSA is also commonly referred to as a controller VM, as illustrated in Figure 1[32]. As mentioned by [PERSON] et al. (2019) [32], the main benefit of the architecture with a controller VM is flexibility. This approach tends to support multiple hypervisors and operate across various platforms. On the other hand, it faces challenges such as resource consumption by the controller VM and its inclusion as an additional component in the data path. However, [PERSON] et al. (2019) [32] highlighted that these challenges tend to be minimized due to advancements in the robustness and capacity of modern CPUs. The second architecture is based on a solution integrated into the hypervisor, as shown in Figure 2. In this case, a kernel module takes responsibility for managing storage. According to [PERSON] et al. (2019) [32], this approach offers a slight performance boost, but at the cost of being limited to a single hypervisor. The authors pointed out that this may result in a situation where the client is locked into expensive software, unable to modify it even if desired. In practice, both approaches have been adopted. In this context, Nutanix and VMware stand out, recognized as leaders according to the Gartner Magic Quadrant [34]. Nutanix uses an architecture based on a controller VM, characterized by a fully software-defined approach with no need for proprietary hardware. Within this model, HCI resource management is performed through an individual VM on each node, forming a physically distributed and logically centralized plan for resource management [35]. On the other hand, VMware adopts an approach integrated into the hypervisor. vSAN is one of VMware's main hyperconvergence solutions, offering a software-defined storage solution that operates integrated with vSphere [36; 37]. In the literature, studies aimed at proposing or evaluating architectures fall into one of the aforementioned classifications. [PERSON] et al. (2019) [38] proposed integrating the GlusterFS distributed file system with the VMware ESXi hypervisor to create a hyperconverged system for hosting Docker containers. In the proposed architecture, a VSA is employed to manage the storage resources of the hyperconvergence solution. Each VSA forms a cluster and provides its individual resources to create a distributed volume. The resulting virtual volume is then used by the \"Container Engine\" as a storage unit. [PERSON] et al. (2021) [39] proposed the construction of a hyperconverged data center that integrates six essential resources--computing, storage, networking, operations monitoring, and maintenance--into a unified cloud platform. The authors adopted the hypervisor-integrated approach. Management is performed in a unified manner, utilizing a minimal hardware architecture and unified software, eliminating the need to access multiple management interfaces. The system consists of three main layers: the basic layer,  
Figure 1: Hyperconverged infrastructure featuring a controller VM-based architecture [32]. Figure 2: Hyperconverged infrastructure designed with an architecture integrated into the hypervisor [32].