Cloud Storage Controller Using Prediction Algorithms for Data Placement
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Solution Overview
Problem
Current cloud storage methods either incur high costs for maintaining data availability and accessibility or face limitations in access speed and availability when data is stored locally, as users must upload data to the cloud for sharing and access, which is impractical due to internet link speed and device connectivity issues.
Innovation Solution
A cloud storage controller that selectively stores data on cloud storage based on prediction algorithms using user habits and file access patterns, allowing data to be accessed from anywhere while minimizing costs by storing frequently accessed data on the cloud and less frequently accessed data locally.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored locally on devices, then storage cost is reduced, but data accessibility and availability deteriorate when devices are offline or unavailable
Solution Approach 1:
The patent segments data storage across multiple locations (local devices and cloud storage) rather than relying on a single storage location. This allows the system to maintain cost-effectiveness by using local storage while ensuring reliability through cloud backup, resolving the contradiction between storage cost and data accessibility.
Solution Approach 2:
The patent introduces cloud storage as an intermediary between local devices and data access. When devices are offline or unavailable, the cloud storage acts as a mediator that preserves data availability, solving the reliability issue without requiring all data to be stored locally.
2Reliability
If data is stored on cloud network, then data accessibility and availability are improved, but storage cost increases significantly
Solution Approach 1:
The patent applies partial action by storing only critical or frequently accessed data on the cloud network rather than all data. This selective cloud storage approach maintains data accessibility for important files while minimizing storage costs by avoiding unnecessary cloud storage for less important data.
Solution Approach 2:
The patent implements local quality by differentiating storage locations based on data characteristics and access patterns. Frequently accessed or critical data is stored on the cloud, while less important data remains locally stored, optimizing both accessibility and cost effectiveness.
3Reliability
If data is uploaded to cloud for sharing, then data accessibility is improved, but access speed deteriorates due to internet link speed limitations
Solution Approach 1:
The patent segments data access paths into direct local access (for speed-critical operations) and cloud access (for availability). By maintaining local copies of data, the system enables fast access when needed while still providing cloud accessibility for sharing and backup, resolving the speed-availability contradiction.
Solution Approach 2:
The patent implements preliminary action by pre-loading or caching frequently accessed data locally before it is needed. This allows the system to provide fast local access for commonly used data while maintaining cloud synchronization for availability, reducing the impact of internet speed limitations.
Data Source
AI summary
A cloud computing network device is disclosed. The device is configured to generate output data based on input data, wherein the output data is indicative of the input data, cause data indicative of the input data to be stored in a memory, and respond to instructions to access the input data by accessing the data stored in the memory.