CLOUD-BASED DISTRIBUTED DATA BACKUP AND RECOVERY SYSTEM

Abstract

The present invention relates to a cloud-based distributed data backup and recovery system that enhances data protection, fault tolerance, and recovery speed by leveraging multiple geographically distributed cloud storage nodes. The system intelligently distributes and replicates backup data across these nodes, ensuring high availability and minimizing the risk of data loss due to localized failures. It incorporates adaptive backup scheduling, secure encryption, and automated recovery mechanisms to provide efficient and cost-effective solutions for data backup, while ensuring rapid restoration of data in the event of failure or disaster.

Specification

Description:
The embodiments of the present invention generally relates to the field of data backup and recovery systems, specifically to cloud-based distributed systems that facilitate the backup and recovery of data across multiple geographically distributed storage nodes. More particularly, it pertains to systems that use advanced algorithms to distribute, replicate, and recover data in a fault-tolerant, efficient, and secure manner to ensure high availability and minimize data loss in case of system failures or disasters.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.

Traditional data backup systems often rely , Claims:
1. A cloud-based distributed data backup and recovery system comprising:
a plurality of geographically distributed cloud storage nodes for storing backup data;
a data backup algorithm that selects an optimal storage location for data across the cloud nodes;
an adaptive backup scheduling mechanism that determines the backup frequency and method based on system performance and user preferences;
a data recovery module that retrieves backup data from one or more cloud nodes in the event of data loss or corruption;
an automated fault detection and recovery system for identifying data inconsistencies and ensuring backup consistency across cloud nodes.

2. The system of claim 1, wherein the data backup algorithm utilizes a distributed hash table (DHT) to store backup data and ensure fault tolerance across the cloud storage nodes.

3. The system of claim 1, wherein the adaptive backup scheduling mechanism incorporates machine learning techniques to optimize backup schedules based on historical data and system load.

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