Storage Utility Network Centralized Data Processing
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Solution Overview
Problem
Current data storage systems face inefficiencies in handling large volumes of data, leading to high operating costs, data duplication, inconsistencies, and latency issues across multiple data centers, which hinder data accessibility and availability.
Innovation Solution
A scalable storage utility network (SUN) is introduced, featuring an ingestion API for data processing, a caching layer for real-time data storage, and a pull API for consumers, utilizing virtual machines and geographically distributed databases to ensure low latency and high availability, with load balancing and data replication across centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple data centers are used to provide access to large amounts of data, then data accessibility is improved, but operating costs increase and data inconsistencies occur
Solution Approach 1:
The patent consolidates multiple distributed data centers into a single centralized data center that handles all data storage and processing operations. This merging eliminates the need for multiple separate facilities, reducing operating costs while maintaining data accessibility through centralized management and unified data architecture.
Solution Approach 2:
The centralized data center is designed to perform multiple functions including data ingestion, processing, storage, and distribution within a single facility. This multi-functional approach replaces the need for specialized multiple data centers, reducing complexity and operational costs while providing comprehensive data access capabilities.
2Quantity of substance
If multiple data centers are used to store data, then data storage capacity is improved, but data duplication and inconsistencies increase
Solution Approach 1:
The patent merges multiple data storage operations into a single centralized data center with a unified data architecture. This eliminates data duplication across multiple centers and ensures data consistency through centralized control, while still providing adequate storage capacity through scalable infrastructure within the single facility.
3Productivity
If conventional data centers process large amounts of data, then data processing volume is improved, but latencies increase that adversely affect data availability
Solution Approach 1:
The patent implements a caching layer that pre-loads and stores frequently accessed processed data before it is requested by consumers. This preliminary action reduces the time required to retrieve data during peak demand periods, maintaining high processing volume while minimizing latency and ensuring data is readily available when needed.
Data Source
AI summary
A storage utility network that includes an ingestion application programming interface (API) mechanism that receives requests from data sources to store data, the requests each containing an indication of a type of data to be stored; at least one data processing engine that is configured to process the type of data, the processing by the at least one data processing engine transforming the data to processed data having a format suitable for consumer use; a plurality of databases that store the processed data and provide the processed data to consumers; and a pull API mechanism that is called by the consumers to retrieve the processed data.