## 3 Reliable Cloud Data Storage: System Model and Problem Formulation  
### System Model  
Reliable cloud data storage has become the most-effective process for managing data. Cloud storage is the process of managing the data remotely and the process of safeguarding the data with third-party servers. To store the data in the cloud, the cloud can give the assurance to improve the security of the data. It considers the four distinct kinds of entities to achieve the storage mechanism. They are \"the data owner, the data user, the cloud user, and the third-party server\". The data owner manages the data to store them in various VMs. The data user can have the capacity to choose the machines where the data are recovered. Simultaneously, the third-party servers are used to check the data integrity frequently.  
Storage mechanism: Cloud storage comprises many devices such as machines. Here, the data storage is nothing but mapping the logical and physical storage. Hence, considering the required components, the storage network may have several constraints while storing the data on the respective servers or VMs. Conversely, the storage process is differentiated into three types, which are explained as follows:  
1. File storage: The files are hierarchically placed in this type. The information is stored in the metadata format of every file. Hence, the files are managed in higher-level abstraction types. Thus, it aids in improving performance.
2. Block storage: Here, the data or files are segmented into different chunks and represented with block addresses. This process does not contain the server for authorization.
3. Object storage: The encapsulation is performed with the object and metadata. Since the data belong to any type, they are distributed over the cloud. This also ensures the scalability and reliability of the system.  
The major goals of designing a reliable cloud data storage system are listed below:  
* Data reliability and availability: By storing the data with more machines or servers, the data user can obtain the encoded data to be deciphered further as the original data. When any of the servers has a fault, they are then used by the other effective servers, thereby enhancing the data integrity and reliability of the cloud network.
* Security: The better system enhances the security level. It also verifies the data integrity and confidentiality, which protects the network from any corrupted services.
* Offline data owner: Once the data are outsourced to a server or machine,there is no need to check the integrity of the stored data in the system.
* Efficiency: Due to this objective, the system's efficacy is reached in terms of less storage space, resolving the overhead problem in communication and computation, and so on.  
Considering the above key points, the proposed reliable data cloud storage system using heuristic development is represented in Figure 1.  
The primary aim of this novel framework is to save cloud data by rectifying the general and structural constraints. Firstly, it considers the components and VMs for storage purposes. Since the components pose various constraints, a new reliable model is introduced. Each piece of cloud data is specified with individual traits, which are then characterized by hardware and software components. Consequently, the new objective function is derived for solving both constraints. The interactions and data instances in the cloud data storage define the structural constraint. Similarly, the allocation rules and device capacity are included in the general constraints. To alleviate the constraint issues, a novel HP-BOA is newly proposed. In the last stage, the performance was measured with metrics, and its simulation results were carried out. Thus, the extensive results proved that the proposed work appropriately stored the cloud data using the components.