Multi-Cloud Data Chunking via Policy Engine
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Solution Overview
Problem
Data security concerns hinder the widespread adoption of cloud storage services, as existing technologies lack effective methods to ensure reliable security across multiple cloud storage providers.
Innovation Solution
A data storage system employing a chunking engine and a policy engine that evaluates storage policies related to cost, security, and network conditions to generate operating parameters for chunking and distributing data across multiple cloud storage providers, ensuring compliance with storage policies and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in a single cloud storage provider, then storage management is simplified, but data security is compromised
Solution Approach 1:
The patent divides data into multiple chunks and distributes them across multiple cloud storage providers. The chunking engine segments files into smaller data chunks that can be stored independently across different cloud providers, enhancing security while managing complexity through automated processes
Solution Approach 2:
The patent combines multiple cloud storage providers into a unified storage system managed by a single data storage system. The policy engine and chunking engine work together to manage data distribution across multiple providers while presenting a simplified interface to users, resolving the contradiction between security through distribution and management simplicity
2Reliability
If data is chunked and distributed across multiple cloud storage providers, then data security is improved, but storage system complexity increases
Solution Approach 1:
The patent introduces a policy engine as an intermediary between the storage system and multiple cloud providers. The policy engine evaluates storage policies, determines optimal cloud providers for each data chunk, and manages the complexity of distribution automatically, reducing the perceived complexity for users while maintaining security benefits
Solution Approach 2:
The system implements feedback mechanisms where the policy engine continuously evaluates storage policies and adjusts data distribution decisions. The system monitors cloud provider performance, security compliance, and cost factors, using this feedback to dynamically optimize data chunk placement across providers, managing complexity through adaptive control
3Reliability
If storage policies are strictly evaluated across multiple cloud providers, then data security compliance is improved, but storage flexibility is reduced
Solution Approach 1:
The patent implements dynamic policy evaluation where the policy engine adapts storage decisions based on current conditions. Storage policies are evaluated in real-time against cloud provider capabilities, allowing the system to maintain compliance while flexibly adjusting data placement strategies based on changing security requirements, costs, and provider performance
Data Source
AI summary
Techniques for chunking data in data storage systems that provide increased data storage security across multiple cloud storage providers. The techniques employ a chunking engine and a policy engine, which evaluates one or more storage policies relating to, for example, cost, security, and/or network conditions in view of services and/or requirements of the multiple cloud storage providers. Having evaluated such storage policies, the policy engine generates and provides operating parameters to the chunking engine, which uses the operating parameters when chunking and/or distributing the data across the multiple cloud storage providers, thereby satisfying the respective storage policies. In this way, users of data storage systems obtain the benefits of cloud storage resources and/or services while reducing their data security concern and optimizing the total cost of data storage.