OPTIMIZING CLOUD BASED DATA STORAGE WITH POLYNOMIAL HASHING AND BUFFERING TECHNIQUES

Abstract

In the ever-evolving landscape of data management, this paper focuses on the secure storage of groundwater level data in the cloud. Leveraging the capabilities of cloud-based databases like Amazon Web Services (AWS) and Microsoft Azure, this phase aims to establish a robust framework that ensures high security, accessibility, and scalability of the stored data. Storing groundwater level data in the cloud offers a myriad of advantages. It guarantees easy and efficient access to the data from any corner of the globe, enabling real-time analysis and visualization. Additionally, cloud storage provides a secure backup mechanism, safeguarding the data against loss or corruption incidents. This abstract highlights the implementation of a cutting-edge buffering polynomial hashing algorithm, designed to enhance the security of the stored data, ensuring its integrity and confidentiality. The utilization of cloud-based solutions not only simplifies data accessibility but also empowers researchers and stakeholders with real-time insights into groundwater level patterns and trends. Through the integration of advanced data analytics tools, the stored data can be meticulously analyzed, unveiling valuable insights that are instrumental in decision-making processes related to water resource management and environmental conservation.

Keywords: Amazon Web Services, Cloud Storage, Cloud-Based Databases, High Security, Secure Storage